FRESH-notebook.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction\n",
    "**This notebook aims at demonstrating how to leverage workflow provenance (information on data processing chains) with a knowledge graph to produce human and machine -oriented data summaries.** We propose to leverage domain-specific annotation ([EDAM ontology](http://edamontology.org/)) from the bioinformatics tools registry [Bio.Tools](http://bio.tools) to automatically annotate workflow processed data in the form of data summaries. \n",
    "\n",
    "### Contacts\n",
    "  - Alban Gaignard: alban.gaignard@univ-nantes.fr\n",
    "  - Hala Skaf-Molli: hala.skaf@univ-nantes.fr\n",
    "  - Khalid Belhajjame: kbelhajj@googlemail.com\n",
    "\n",
    "### Approach\n",
    "![alt text](approach.png \"Approach\")\n",
    "Here are the main steps of this demonstration : \n",
    "  1. Knowledge graph loading (With assume that a provenance is already available)\n",
    "  1. Machine-oriented provenance mining queries\n",
    "  1. Human-oriented provenance mining queries\n",
    "  \n",
    "### Software dependencies \n",
    "  - [RdfLib](https://rdflib.readthedocs.io/en/stable/) for RDF data management and SPARQL querying\n",
    "  - [NetworkX](https://networkx.github.io/documentation/stable/) for graph visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import display, Markdown, Latex\n",
    "from string import Template\n",
    "import datetime\n",
    "#import requests\n",
    "import json\n",
    "import io\n",
    "\n",
    "import networkx as nx\n",
    "from nxpd import draw\n",
    "\n",
    "from rdflib import ConjunctiveGraph, RDF, RDFS, Namespace\n",
    "\n",
    "def serialize():\n",
    "    print(g.serialize(format='turtle'))\n",
    "\n",
    "def save(filename):\n",
    "    with open(filename, 'w') as f:\n",
    "        g.serialize(f, format='turtle')\n",
    "        \n",
    "def load(filename):\n",
    "    with io.open(filename,'r',encoding='utf8') as f:\n",
    "        g.load(f, format='turtle')  \n",
    "\n",
    "g = ConjunctiveGraph()\n",
    "g.bind('prov', Namespace('http://www.w3.org/ns/prov#'))\n",
    "g.bind('p-plan', Namespace('http://purl.org/net/p-plan#'))\n",
    "g.bind('biotools', Namespace('https://bio.tools/ontology/'))\n",
    "g.bind('mp', Namespace('http://purl.org/mp/'))\n",
    "g.bind('oboInOwl', Namespace('http://www.geneontology.org/formats/oboInOwl#'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Caracteristics of the captured provenance graph"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Size of the provenance graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "555 triples in the provenance graph\n"
     ]
    }
   ],
   "source": [
    "prov_graph = ConjunctiveGraph()\n",
    "prov_graph.bind('prov',Namespace('http://www.w3.org/ns/prov#'))\n",
    "with io.open('provenance.ttl','r',encoding='utf8') as f:\n",
    "    prov_graph.load(f, format='turtle')\n",
    "print(str(len(prov_graph)) + \" triples in the provenance graph\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution of PROV classes "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "\n",
       "| Class name | Number of instances |\n",
       "|------|------|\n",
       "|http://www.w3.org/ns/prov#Entity | 40 | \n",
       "|http://www.w3.org/ns/prov#Activity | 26 | \n",
       "|http://www.w3.org/ns/prov#Person | 1 | \n",
       "|http://www.w3.org/ns/prov#Agent | 1 | \n",
       "|http://www.w3.org/ns/prov#Bundle | 1 | \n"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "q_classes = \"SELECT  ?class (COUNT(?s) AS ?count ) { ?s a ?class } GROUP BY ?class ORDER BY DESC(?count)\"\n",
    "results = prov_graph.query(q_classes)\n",
    "md = \"\"\"\n",
    "| Class name | Number of instances |\n",
    "|------|------|\n",
    "\"\"\" \n",
    "for r in results :\n",
    "    md = md + \"|\" + str(r['class']) + \" | \" + str(r['count']) + \" | \" + \"\\n\"\n",
    "display(Markdown(md))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution of PROV predicates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "\n",
       "| Property name | Number of predicates |\n",
       "|------|------|\n",
       "|http://www.w3.org/ns/prov#wasDerivedFrom | 167 | \n",
       "|http://www.w3.org/ns/prov#used | 100 | \n",
       "|http://www.w3.org/1999/02/22-rdf-syntax-ns#type | 69 | \n",
       "|http://www.w3.org/ns/prov#wasAssociatedWith | 65 | \n",
       "|http://www.w3.org/ns/prov#wasGeneratedBy | 39 | \n",
       "|http://www.w3.org/2000/01/rdf-schema#label | 39 | \n",
       "|http://www.w3.org/ns/prov#startedAtTime | 26 | \n",
       "|http://www.w3.org/ns/prov#endedAtTime | 26 | \n",
       "|http://www.w3.org/2000/01/rdf-schema#comment | 22 | \n",
       "|http://www.w3.org/ns/prov#generatedAtTime | 1 | \n",
       "|http://www.w3.org/ns/prov#wasAttributedTo | 1 | \n"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "q_properties  = \" SELECT  ?p (COUNT(?s) AS ?count ) { ?s ?p ?o } GROUP BY ?p ORDER BY DESC(?count)\"\n",
    "results = prov_graph.query(q_properties)\n",
    "md = \"\"\"\n",
    "| Property name | Number of predicates |\n",
    "|------|------|\n",
    "\"\"\" \n",
    "for r in results :\n",
    "    md = md + \"|\" + str(r['p']) + \" | \" + str(r['count']) + \" | \" + \"\\n\"\n",
    "display(Markdown(md))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Loading the Knowledge Graph\n",
    "This graph is built from: \n",
    "   - the workflow run as a provenance graph (PROV-O): `provenance.ttl`\n",
    "   - a dump of the [bio.tools](http://bio.tools) registry: `biotools-dump-latest.ttl`\n",
    "   - the [EDAM](http://edamontology.org) ontology: `EDAM.owl`\n",
    "\n",
    "Data loading takes around 20s. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "provenance.ttl loaded\n",
      "biotools-dump-latest.ttl loaded\n",
      "edam.owl loaded\n",
      "\n",
      "Graph size: 203171 triples\n",
      "CPU times: user 12.7 s, sys: 109 ms, total: 12.8 s\n",
      "Wall time: 12.8 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "experiment = \"\"\"\n",
    "@prefix mp:  <http://purl.org/mp/> .\n",
    "@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .\n",
    "@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .\n",
    "\n",
    "_:mp1 rdf:type mp:Micropublication ;\n",
    "    mp:argues _:claim1 .\n",
    "\n",
    "_:claim1 rdf:type mp:Claim ;\n",
    "    mp:statement \"Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm\" .\n",
    "\"\"\"\n",
    "g.parse(data=experiment, format='turtle')\n",
    "\n",
    "load('provenance.ttl')\n",
    "print('provenance.ttl loaded')\n",
    "\n",
    "load('biotools-dump-latest.ttl')\n",
    "print('biotools-dump-latest.ttl loaded')\n",
    "\n",
    "with io.open('EDAM.owl','r',encoding='utf8') as f:\n",
    "        g.load(f, format='xml')\n",
    "print('edam.owl loaded')\n",
    "\n",
    "print()\n",
    "print('Graph size: %s triples' % len(g))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Human-oriented data summaries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sentence-based data explanations  \n",
    "Here, the goal is to describe a piece of data with the consensual definition of **what** does the tool that generates this piece of data.  \n",
    "Technically, this is done with a SPARQL query that combine the provenance information (*prov:wasGeneratedBy*), the description of the tool (*biotools:has_function*), and the domain knowledge on the nature of the processing (*oboInOwl:hasDefinition*). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/BAM/Sample1.realign.bai` **results from tool** gatk2_indel_realigner-IP **which** Locally align two or more molecular sequences."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.combined.g.vcf.gz.tbi` **results from tool** gatk2_variant_combine-IP **which** Merge two or more (typically overlapping) molecular sequences."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/BAM/Sample1.recal.table` **results from tool** gatk2_base_recalibrator-IP **which** Analyse one or more known molecular sequences."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.indel.recal.select.vcf.gz.tbi` **results from tool** gatk2_variant_select-IP **which** Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.recal.combined.vcf.gz.tbi` **results from tool** gatk2_variant_combine-IP **which** Merge two or more (typically overlapping) molecular sequences."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.recal.combined.vcf.gz` **results from tool** gatk2_variant_combine-IP **which** Merge two or more (typically overlapping) molecular sequences."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/BAM/Sample1.realign.intervals` **results from tool** gatk2_realigner_target_creator-IP **which** Locally align two or more molecular sequences."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.snv.recal.select.vcf.gz.tbi` **results from tool** gatk2_variant_select-IP **which** Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/BAM/Sample1.markdup.bam` **results from tool** MarkDuplicates (IP) **which** Predict, recognise and identify positional features in molecular sequences such as key functional sites or regions."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/BAM/Sample1.p1.aligned.sam` **results from tool** BWA (cloudIFB) **which** Construct some data entity."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/BAM/Sample1.p1.aligned.sam` **results from tool** BWA (cloudIFB) **which** Generate an index of a genome sequence."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/BAM/Sample1.p1.aligned.sam` **results from tool** BWA (cloudIFB) **which** Align short oligonucleotide sequences (reads) to a larger (genomic) sequence."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/BAM/Sample1.p1.aligned.sam` **results from tool** BWA (cloudIFB) **which** Align (identify equivalent sites within) molecular sequences."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.recal.combined.annot.gnomad.vcf.gz` **results from tool** gatk2_variant_annotator-IP **which** Predict the effect or function of an individual single nucleotide polymorphism (SNP)."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/BAM/Sample1.p1.sorted.bam` **results from tool** samtools_sort-IP **which** Reformat a file of data (or equivalent entity in memory)."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.combined.g.vcf.gz` **results from tool** gatk2_variant_combine-IP **which** Merge two or more (typically overlapping) molecular sequences."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.snv.recal.filter.vcf.gz.tbi` **results from tool** gatk2_variant_filtration-IP **which** Analyse a genetic variation, for example to annotate its location, alleles, classification, and effects on individual transcripts predicted for a gene model."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.snv.recal.filter.vcf.gz.tbi` **results from tool** gatk2_variant_filtration-IP **which** Filter a set of files or data items according to some property."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `BED/capture.extended1000.bed` **results from tool** bedtools_mergebedgraph-IP **which** Merge two or more (typically overlapping) molecular sequences."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.recal.combined.annot.gnomad.vcf.gz.tbi` **results from tool** gatk2_variant_annotator-IP **which** Predict the effect or function of an individual single nucleotide polymorphism (SNP)."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.genotyped.vcf.gz` **results from tool** gatk2_unified_genotyper-IP **which** Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.genotyped.vcf.gz` **results from tool** gatk2_unified_genotyper-IP **which** Identify insertion, deletion and duplication events from a sequence alignment."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.indel.recal.select.vcf.gz` **results from tool** gatk2_variant_select-IP **which** Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `BED/capture.bed` **results from tool** bedtools_mergebedgraph-IP **which** Merge two or more (typically overlapping) molecular sequences."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.snv.recal.select.vcf.gz` **results from tool** gatk2_variant_select-IP **which** Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.snv.recal.filter.vcf.gz` **results from tool** gatk2_variant_filtration-IP **which** Analyse a genetic variation, for example to annotate its location, alleles, classification, and effects on individual transcripts predicted for a gene model."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.snv.recal.filter.vcf.gz` **results from tool** gatk2_variant_filtration-IP **which** Filter a set of files or data items according to some property."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/BAM/Sample1.realign.bam` **results from tool** gatk2_indel_realigner-IP **which** Locally align two or more molecular sequences."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.genotyped.vcf.gz.tbi` **results from tool** gatk2_unified_genotyper-IP **which** Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.genotyped.vcf.gz.tbi` **results from tool** gatk2_unified_genotyper-IP **which** Identify insertion, deletion and duplication events from a sequence alignment."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/BAM/Sample1.merged.bam` **results from tool** Picard **which** Analyse a genetic variation, for example to annotate its location, alleles, classification, and effects on individual transcripts predicted for a gene model."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/BAM/Sample1.final.bai` **results from tool** gatk2_print_reads-IP **which** Counting and summarising the number of short sequence reads that map to genomic features."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/VCF/Sample1.hapcaller.g.vcf` **results from tool** gatk2_haplotype_caller-IP **which** Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.indel.recal.filter.vcf.gz` **results from tool** gatk2_variant_filtration-IP **which** Analyse a genetic variation, for example to annotate its location, alleles, classification, and effects on individual transcripts predicted for a gene model."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.indel.recal.filter.vcf.gz` **results from tool** gatk2_variant_filtration-IP **which** Filter a set of files or data items according to some property."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/QC/Sample1.markdup.metrics` **results from tool** MarkDuplicates (IP) **which** Predict, recognise and identify positional features in molecular sequences such as key functional sites or regions."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/BAM/Sample1.final.bam` **results from tool** gatk2_print_reads-IP **which** Counting and summarising the number of short sequence reads that map to genomic features."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/BAM/Sample1.merged.bai` **results from tool** Picard **which** Analyse a genetic variation, for example to annotate its location, alleles, classification, and effects on individual transcripts predicted for a gene model."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.indel.recal.filter.vcf.gz.tbi` **results from tool** gatk2_variant_filtration-IP **which** Analyse a genetic variation, for example to annotate its location, alleles, classification, and effects on individual transcripts predicted for a gene model."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `VCF/hapcaller.indel.recal.filter.vcf.gz.tbi` **results from tool** gatk2_variant_filtration-IP **which** Filter a set of files or data items according to some property."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/VCF/Sample1.hapcaller.g.vcf.idx` **results from tool** gatk2_haplotype_caller-IP **which** Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "The file `Samples/Sample1/BAM/Sample1.markdup.bai` **results from tool** MarkDuplicates (IP) **which** Predict, recognise and identify positional features in molecular sequences such as key functional sites or regions."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       " **It was produced in the context of** Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 121 ms, sys: 21 ms, total: 142 ms\n",
      "Wall time: 139 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "query = \"\"\"\n",
    "    SELECT ?d_label ?title ?f_def ?st WHERE {\n",
    "        ?d rdf:type prov:Entity ;\n",
    "           prov:wasGeneratedBy ?x ;\n",
    "           prov:wasAssociatedWith ?tool ;\n",
    "           rdfs:label ?d_label .\n",
    "        \n",
    "        ?tool dc:title ?title ;\n",
    "            biotools:has_function ?f .\n",
    "            \n",
    "        ?f rdfs:label ?f_label ;\n",
    "            oboInOwl:hasDefinition ?f_def .\n",
    "            \n",
    "        ?c rdf:type mp:Claim ;    \n",
    "            mp:statement ?st .\n",
    "    }\n",
    "\"\"\"\n",
    "\n",
    "results = g.query(query)\n",
    "for r in results :\n",
    "    display(Markdown('The file `' + str(r['d_label']) + '`'\n",
    "                     +' **results from tool** ' + str(r['title']) \n",
    "                     + ' **which** ' + str(r['f_def'])))\n",
    "    display(Markdown(' **It was produced in the context of** ' + str(r['st']) ))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Summary graph of  the main processing steps\n",
    "### Here, the goal is to display a graph of domain-specific terms, describing the workflow processing steps. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges = []\n",
    "\n",
    "query = \"\"\"\n",
    "    CONSTRUCT {\n",
    "        ?x2 p-plan:wasPreceededBy ?x1 .\n",
    "        ?x2 prov:wasAssociatedWith ?t2 .\n",
    "        ?x1 prov:wasAssociatedWith ?t1 .\n",
    "        ?t1 biotools:has_function ?f1 .\n",
    "        ?f1 rdfs:label ?f1_label .\n",
    "        ?t2 biotools:has_function ?f2 .\n",
    "        ?f2 rdfs:label ?f2_label .\n",
    "    } WHERE {\n",
    "        ?d2 prov:wasDerivedFrom ?d1 .\n",
    "        \n",
    "        ?d2 prov:wasGeneratedBy ?x2 ;\n",
    "           prov:wasAssociatedWith ?t2 ;\n",
    "           rdfs:label ?d2_label .\n",
    "        \n",
    "        ?d1 prov:wasGeneratedBy ?x1 ;\n",
    "           prov:wasAssociatedWith ?t1 ;\n",
    "           rdfs:label ?d1_label .\n",
    "        \n",
    "        ?t1 biotools:has_function ?f1 .\n",
    "        ?f1 rdfs:label ?f1_label .\n",
    "        \n",
    "        ?t2 biotools:has_function ?f2 .\n",
    "        ?f2 rdfs:label ?f2_label .\n",
    "    }\n",
    "\"\"\"\n",
    "\n",
    "abstract_wf = ConjunctiveGraph()\n",
    "abstract_wf.bind('prov',Namespace('http://www.w3.org/ns/prov#'))\n",
    "abstract_wf.bind('p-plan',Namespace('http://purl.org/net/p-plan#'))\n",
    "abstract_wf.bind('biotools',Namespace('https://bio.tools/ontology/'))\n",
    "\n",
    "results = g.query(query)\n",
    "for r in results :\n",
    "    abstract_wf.add(r)\n",
    "\n",
    "abstract_wf.serialize(destination='abstract_wf.ttl', format='turtle')\n",
    "\n",
    "vis_query = \"\"\"\n",
    "    SELECT ?f1_label ?f2_label WHERE {\n",
    "        ?x2 p-plan:wasPreceededBy ?x1 .\n",
    "        ?x2 prov:wasAssociatedWith ?t2 .\n",
    "        ?x1 prov:wasAssociatedWith ?t1 .\n",
    "        ?t1 biotools:has_function ?f1 .\n",
    "        ?f1 rdfs:label ?f1_label .\n",
    "        ?t2 biotools:has_function ?f2 .\n",
    "        ?f2 rdfs:label ?f2_label .\n",
    "    }\n",
    "\"\"\"\n",
    "\n",
    "results = abstract_wf.query(vis_query)\n",
    "for r in results :\n",
    "    edges.append((r['f1_label'], r['f2_label']))\n",
    "\n",
    "G = nx.DiGraph()\n",
    "G.graph['dpi'] = 120\n",
    "G.graph['layout'] = 'dot'\n",
    "G.add_edges_from(edges)\n",
    "\n",
    "#pos = nx.nx_agraph.graphviz_layout(G, prog=\"dot\")\n",
    "#nx.draw(G, pos)\n",
    "draw(G, show='ipynb')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Finally we show in this last cell how we can document intermediate data with the conceptual processing they result from, again with domain-specific terms. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 224 ms, sys: 5.58 ms, total: 230 ms\n",
      "Wall time: 229 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "pattern_intermediate = \"Sample1.final.bam\"\n",
    "pattern_final = \"hapcaller.recal.combined.annot.gnomad.vcf.gz\"\n",
    "\n",
    "query = \"\"\"\n",
    "    CONSTRUCT {\n",
    "        ?x2 p-plan:wasPreceededBy ?x1 .\n",
    "        ?x2 prov:wasAssociatedWith ?t2 .\n",
    "        ?x1 prov:wasAssociatedWith ?t1 .\n",
    "        ?t1 biotools:has_function ?f1 .\n",
    "        ?f1 rdfs:label ?f1_label .\n",
    "        ?t2 biotools:has_function ?f2 .\n",
    "        ?f2 rdfs:label ?f2_label .\n",
    "        \n",
    "        ?d rdf:type prov:Entity ;\n",
    "               prov:wasGeneratedBy ?x ;\n",
    "               prov:wasAssociatedWith ?tool ;\n",
    "               rdfs:label ?d_label .\n",
    "    } WHERE {\n",
    "        {\n",
    "            ?d2 prov:wasDerivedFrom ?d1 .\n",
    "        \n",
    "            ?d2 prov:wasGeneratedBy ?x2 ;\n",
    "               prov:wasAssociatedWith ?t2 ;\n",
    "               rdfs:label ?d2_label .\n",
    "        \n",
    "            ?d1 prov:wasGeneratedBy ?x1 ;\n",
    "               prov:wasAssociatedWith ?t1 ;\n",
    "               rdfs:label ?d1_label .\n",
    "        \n",
    "            ?t1 biotools:has_function ?f1 .\n",
    "            ?f1 rdfs:label ?f1_label .\n",
    "        \n",
    "            ?t2 biotools:has_function ?f2 .\n",
    "            ?f2 rdfs:label ?f2_label .\n",
    "        } UNION {\n",
    "            ?d rdf:type prov:Entity ;\n",
    "               prov:wasGeneratedBy ?x ;\n",
    "               prov:wasAssociatedWith ?tool ;\n",
    "               rdfs:label ?d_label .\n",
    "            FILTER (regex(?d_label, \\\"\"\"\" + pattern_intermediate + \"\"\"\\\", \"i\")) .\n",
    "        }\n",
    "    }\n",
    "\"\"\"\n",
    "\n",
    "abstract_wf = ConjunctiveGraph()\n",
    "abstract_wf.bind('prov',Namespace('http://www.w3.org/ns/prov#'))\n",
    "abstract_wf.bind('p-plan',Namespace('http://purl.org/net/p-plan#'))\n",
    "abstract_wf.bind('biotools',Namespace('https://bio.tools/ontology/'))\n",
    "\n",
    "results = g.query(query)\n",
    "for r in results :\n",
    "    abstract_wf.add(r)\n",
    "\n",
    "abstract_wf.serialize(destination='abstract_wf.ttl', format='turtle')\n",
    "\n",
    "vis_query1 = \"\"\"\n",
    "    SELECT ?f1_label ?f2_label WHERE {\n",
    "        ?x2 p-plan:wasPreceededBy ?x1 .\n",
    "        ?x2 prov:wasAssociatedWith ?t2 .\n",
    "        ?x1 prov:wasAssociatedWith ?t1 .\n",
    "        ?t1 biotools:has_function ?f1 .\n",
    "        ?f1 rdfs:label ?f1_label .\n",
    "        ?t2 biotools:has_function ?f2 .\n",
    "        ?f2 rdfs:label ?f2_label .\n",
    "    }\n",
    "\"\"\"\n",
    "\n",
    "edges = []\n",
    "results = abstract_wf.query(vis_query1)\n",
    "for r in results :\n",
    "    edges.append((r['f1_label'], r['f2_label']))\n",
    "\n",
    "vis_query2 = \"\"\"\n",
    "    SELECT ?d_label ?tool ?f_label WHERE {\n",
    "        ?d rdf:type prov:Entity ;\n",
    "            prov:wasGeneratedBy ?x ;\n",
    "            prov:wasAssociatedWith ?tool ;\n",
    "            rdfs:label ?d_label .\n",
    "        ?tool biotools:has_function ?f .\n",
    "        ?f rdfs:label ?f_label .\n",
    "    }\n",
    "\"\"\"\n",
    "\n",
    "edges_data = []\n",
    "nodes_data = []\n",
    "results = abstract_wf.query(vis_query2)\n",
    "for r in results :\n",
    "    edges_data.append((r['f_label'], r['d_label']))\n",
    "    nodes_data.append(r['d_label'])\n",
    "\n",
    "G = nx.DiGraph()\n",
    "G.graph['dpi'] = 120\n",
    "G.graph['layout'] = 'dot'\n",
    "G.add_nodes_from(nodes_data, color='blue', shape=\"note\")\n",
    "G.add_edges_from(edges)\n",
    "G.add_edges_from(edges_data, color='blue', style=\"dashed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 10.8 ms, sys: 6.48 ms, total: 17.2 ms\n",
      "Wall time: 72.8 ms\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#%time draw(G, filename='plot.pdf', format='pdf')\n",
    "%time draw(G, show='ipynb')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. Machine-oriented summaries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we assemble a [NanoPublication](http://nanopub.org/wordpress/) aimed at reporting, from the provenance, what has been done on data, with domain-specific annotations. The SPARQL CONSTRUCT query produces RDF triples representing the workflow steps ([P-Plan ontology](http://www.opmw.org/model/p-plan/)) and their nature in terms of [EDAM operations](http://edamontology.org). These triples form the *Assertion* named graph of the publication. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "@prefix : <http://example.org/pub1#> .\n",
      "@prefix ex: <http://example.org/> .\n",
      "@prefix np:  <http://www.nanopub.org/nschema#> .\n",
      "@prefix prov: <http://www.w3.org/ns/prov#> . \n",
      "@prefix xsd:  <http://www.w3.org/2001/XMLSchema#> .\n",
      "\n",
      ":head {\n",
      "    ex:pub1 a np:Nanopublication .\n",
      "    ex:pub1 np:hasAssertion :assertion .\n",
      "    ex:pub1 np:hasProvenance :provenance .\n",
      "    ex:pub1 np:hasPublicationInfo :pubInfo .\n",
      "}\n",
      "\n",
      ":assertion {\n",
      "    <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/gatk2_variant_select-ip> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/gatk2_print_reads-ip> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/samtools_sort-ip> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_0232> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/gatk2_variant_filtration-ip> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_0495> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/markduplicates_ip> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_3227> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_0232> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_3695> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/bedtools_mergebedgraph-ip> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_0495> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_3211> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/gatk2_indel_realigner-ip> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/bwa_cloudifb> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/gatk2_variant_combine-ip> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/gatk2_realigner_target_creator-ip> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/gatk2_base_recalibrator-ip> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/gatk2_variant_annotator-ip> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_0232> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_3695> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_3198> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/gatk2_variant_filtration-ip> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_3197> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/picard_tools> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_3227> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_3793> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_0232> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_0335> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_0292> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/gatk2_variant_combine-ip> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_2403> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_3661> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/bedtools_mergebedgraph-ip> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_3429> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_3227> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/gatk2_variant_select-ip> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_0452> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_3227> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-6fc46366-474b-4cc6-8e69-fbb54c014881> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/gatk2_haplotype_caller-ip> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_3197> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> .\n",
      "\t<http://snakemake-provenance#activity-3ecb4c10-dffd-4d1c-9e61-d438b84a874b> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b4de3b83-1cc6-4f48-ad48-540d300cf703> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://bio.tools/gatk2_unified_genotyper-ip> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-133b295b-41ad-40d1-be31-3d9f1821e220> .\n",
      "\t<http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e42b45fa-7c20-461c-bf0f-9c97b4c6670a> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-fcd2483e-6a4a-4c25-ac62-da88da13480e> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-d41f5a7f-5523-487f-b092-8be4c1b7b42f> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_0253> .\n",
      "\t<http://snakemake-provenance#activity-1df41f0b-a86f-41eb-95cf-cd41c2cb9a85> <https://bio.tools/ontology/has_function> <http://edamontology.org/operation_3197> .\n",
      "\t<http://snakemake-provenance#activity-3b3476df-63c8-47c6-b7df-18a96b8ca4b9> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/p-plan#Step> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-b28835ac-68b5-4082-8c4a-5eed5794d445> .\n",
      "\t<http://snakemake-provenance#activity-df1e815f-8dd4-4493-85b9-a26a8a2ca7ad> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-b25534f0-ee06-4a8d-ae9d-e42bb80732b1> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-2de11e77-c462-40d3-b93c-550eb2a65a20> .\n",
      "\t<http://snakemake-provenance#activity-c7088668-7613-43c4-a6ed-9a10b163b0de> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> .\n",
      "\t<http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-c17a6f7a-d53d-4c53-a523-b03f23b46fda> .\n",
      "\t<http://snakemake-provenance#activity-7a09a3bb-e940-4d70-b242-48ce8fca4dd9> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-91c40a1e-45f0-47c2-a19d-3e6d47d993ed> .\n",
      "\t<http://snakemake-provenance#activity-e5a4336a-3495-4821-9bd2-24d444b61637> <http://purl.org/net/p-plan#wasPreceededBy> <http://snakemake-provenance#activity-dde929a6-b8c0-42a7-a051-f02a370a07ab> .\n",
      "}\n",
      "\n",
      ":provenance {\n",
      "    :assertion prov:generatedAtTime \"2021-06-30T23:38:51.013795\"^^xsd:dateTime .\n",
      "    :assertion prov:wasDerivedFrom :experiment .\n",
      "    :assertion prov:wasAttributedTo <https://orcid.org/0000-0002-3597-8557> .\n",
      "}\n",
      "\n",
      ":pubInfo {\n",
      "    ex:pub1 prov:wasAttributedTo <https://orcid.org/0000-0002-3597-8557> .\n",
      "}\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "my_ORCID = \"0000-0002-3597-8557\"\n",
    "\n",
    "wf_assertions = []\n",
    "\n",
    "np_wf_query = \"\"\"\n",
    "    CONSTRUCT {\n",
    "        ?x2 p-plan:wasPreceededBy ?x1 .\n",
    "        ?x2 rdf:type p-plan:Step ;\n",
    "            biotools:has_function ?f2 ; \n",
    "            rdfs:seeAlso ?t2 .\n",
    "        ?x1 rdf:type p-plan:Step ;\n",
    "            biotools:has_function ?f1 ; \n",
    "            rdfs:seeAlso ?t1 .\n",
    "    } WHERE {\n",
    "        ?x2 rdf:type prov:Activity ;\n",
    "            prov:wasAssociatedWith ?t2 .\n",
    "        ?x1 rdf:type prov:Activity ;\n",
    "            prov:wasAssociatedWith ?t1 .\n",
    "        ?t1 biotools:has_function ?f1 .\n",
    "        ?f1 rdfs:label ?f1_label .\n",
    "        ?t2 biotools:has_function ?f2 .\n",
    "        ?f2 rdfs:label ?f2_label .\n",
    "    } \n",
    "\"\"\"\n",
    "\n",
    "results = g.query(np_wf_query)\n",
    "for r in results :\n",
    "    wf_assertions.append('<'+str(r[0])+'>' \" \" + '<'+str(r[1])+'>' + \" \" + '<'+str(r[2])+'> .')\n",
    "\n",
    "nanopub_template = \"\"\"\n",
    "\n",
    "@prefix : <http://example.org/pub1#> .\n",
    "@prefix ex: <http://example.org/> .\n",
    "@prefix np:  <http://www.nanopub.org/nschema#> .\n",
    "@prefix prov: <http://www.w3.org/ns/prov#> . \n",
    "@prefix xsd:  <http://www.w3.org/2001/XMLSchema#> .\n",
    "\n",
    ":head {\n",
    "    ex:pub1 a np:Nanopublication .\n",
    "    ex:pub1 np:hasAssertion :assertion .\n",
    "    ex:pub1 np:hasProvenance :provenance .\n",
    "    ex:pub1 np:hasPublicationInfo :pubInfo .\n",
    "}\n",
    "\n",
    ":assertion {\n",
    "    $Assertion\n",
    "}\n",
    "\n",
    ":provenance {\n",
    "    :assertion prov:generatedAtTime \\\"\"\"\"+datetime.datetime.now().isoformat()+\"\"\"\\\"^^xsd:dateTime .\n",
    "    :assertion prov:wasDerivedFrom :experiment .\n",
    "    :assertion prov:wasAttributedTo <https://orcid.org/\"\"\"+my_ORCID+\"\"\"> .\n",
    "}\n",
    "\n",
    ":pubInfo {\n",
    "    ex:pub1 prov:wasAttributedTo <https://orcid.org/\"\"\"+my_ORCID+\"\"\"> .\n",
    "}\n",
    "\n",
    "\"\"\"\n",
    "\n",
    "assert_graph = ('\\n\\t').join(wf_assertions)\n",
    "\n",
    "np = Template(nanopub_template)\n",
    "np = np.substitute(Assertion = assert_graph)\n",
    "\n",
    "print(np)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now we focus more on data and associate the domain annotations gathered from the tools to each processed data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "@prefix : <http://example.org/pub1#> .\n",
      "@prefix ex: <http://example.org/> .\n",
      "@prefix np:  <http://www.nanopub.org/nschema#> .\n",
      "@prefix prov: <http://www.w3.org/ns/prov#> . \n",
      "@prefix xsd:  <http://www.w3.org/2001/XMLSchema#> .\n",
      "\n",
      ":head {\n",
      "    ex:pub1 a np:Nanopublication .\n",
      "    ex:pub1 np:hasAssertion :assertion .\n",
      "    ex:pub1 np:hasProvenance :provenance .\n",
      "    ex:pub1 np:hasPublicationInfo :pubInfo .\n",
      "}\n",
      "\n",
      ":assertion {\n",
      "    <http://snakemake-provenance/Samples/Sample1/BAM/Sample1.p1.aligned.sam> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0292> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.merged.bam> <http://www.w3.org/2000/01/rdf-schema#comment> <Analyse a genetic variation, for example to annotate its location, alleles, classification, and effects on individual transcripts predicted for a gene model.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.genotyped.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#comment> <Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.recal.combined.annot.gnomad.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#comment> <Predict the effect or function of an individual single nucleotide polymorphism (SNP).> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.p1.sorted.bam> <http://www.w3.org/2000/01/rdf-schema#comment> <Reformat a file of data (or equivalent entity in memory).> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.snv.recal.filter.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#comment> <Filter a set of files or data items according to some property.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/VCF/Sample1.hapcaller.g.vcf.idx> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3227> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.snv.recal.select.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#comment> <Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.merged.bam> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3197> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.p1.aligned.sam> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3429> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.genotyped.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#comment> <Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.merged.bai> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3197> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.markdup.bai> <http://www.w3.org/2000/01/rdf-schema#comment> <Predict, recognise and identify positional features in molecular sequences such as key functional sites or regions.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.snv.recal.select.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3227> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/VCF/Sample1.hapcaller.g.vcf> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3227> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/QC/Sample1.markdup.metrics> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0253> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.combined.g.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0232> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.final.bai> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3793> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.indel.recal.select.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#comment> <Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.realign.bai> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0495> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.combined.g.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#comment> <Merge two or more (typically overlapping) molecular sequences.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.combined.g.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0232> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.p1.aligned.sam> <http://www.w3.org/2000/01/rdf-schema#comment> <Generate an index of a genome sequence.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.markdup.bai> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0253> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.realign.intervals> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0495> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.p1.aligned.sam> <http://www.w3.org/2000/01/rdf-schema#comment> <Align (identify equivalent sites within) molecular sequences.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.snv.recal.filter.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3695> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.final.bam> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3793> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.p1.aligned.sam> <http://www.w3.org/2000/01/rdf-schema#comment> <Align short oligonucleotide sequences (reads) to a larger (genomic) sequence.> .\n",
      "\t<http://snakemake-provenance/BED/capture.extended1000.bed> <http://www.w3.org/2000/01/rdf-schema#comment> <Merge two or more (typically overlapping) molecular sequences.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.p1.aligned.sam> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3198> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.recal.combined.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0232> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.recal.combined.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#comment> <Merge two or more (typically overlapping) molecular sequences.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.indel.recal.filter.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3197> .\n",
      "\t<http://snakemake-provenance/BED/capture.bed> <http://www.w3.org/2000/01/rdf-schema#comment> <Merge two or more (typically overlapping) molecular sequences.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/QC/Sample1.markdup.metrics> <http://www.w3.org/2000/01/rdf-schema#comment> <Predict, recognise and identify positional features in molecular sequences such as key functional sites or regions.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.snv.recal.filter.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#comment> <Analyse a genetic variation, for example to annotate its location, alleles, classification, and effects on individual transcripts predicted for a gene model.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.recal.combined.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#comment> <Merge two or more (typically overlapping) molecular sequences.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.snv.recal.filter.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3197> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.p1.sorted.bam> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0335> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.genotyped.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3227> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.genotyped.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0452> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.indel.recal.filter.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3695> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.snv.recal.filter.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3695> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.indel.recal.filter.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3197> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.indel.recal.filter.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#comment> <Analyse a genetic variation, for example to annotate its location, alleles, classification, and effects on individual transcripts predicted for a gene model.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.indel.recal.select.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3227> .\n",
      "\t<http://snakemake-provenance/BED/capture.extended1000.bed> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0232> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.final.bai> <http://www.w3.org/2000/01/rdf-schema#comment> <Counting and summarising the number of short sequence reads that map to genomic features.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.genotyped.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3227> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.combined.g.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#comment> <Merge two or more (typically overlapping) molecular sequences.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.indel.recal.filter.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#comment> <Filter a set of files or data items according to some property.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.genotyped.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0452> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/VCF/Sample1.hapcaller.g.vcf.idx> <http://www.w3.org/2000/01/rdf-schema#comment> <Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.p1.aligned.sam> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3211> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.recal.combined.annot.gnomad.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3661> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.recal.combined.annot.gnomad.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#comment> <Predict the effect or function of an individual single nucleotide polymorphism (SNP).> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.snv.recal.filter.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3197> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.indel.recal.filter.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3695> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.snv.recal.filter.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#comment> <Analyse a genetic variation, for example to annotate its location, alleles, classification, and effects on individual transcripts predicted for a gene model.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.realign.intervals> <http://www.w3.org/2000/01/rdf-schema#comment> <Locally align two or more molecular sequences.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.indel.recal.filter.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#comment> <Filter a set of files or data items according to some property.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.realign.bam> <http://www.w3.org/2000/01/rdf-schema#comment> <Locally align two or more molecular sequences.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.recal.combined.annot.gnomad.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3661> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.snv.recal.select.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#comment> <Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.realign.bai> <http://www.w3.org/2000/01/rdf-schema#comment> <Locally align two or more molecular sequences.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.realign.bam> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0495> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.final.bam> <http://www.w3.org/2000/01/rdf-schema#comment> <Counting and summarising the number of short sequence reads that map to genomic features.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.recal.table> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_2403> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.merged.bai> <http://www.w3.org/2000/01/rdf-schema#comment> <Analyse a genetic variation, for example to annotate its location, alleles, classification, and effects on individual transcripts predicted for a gene model.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.recal.table> <http://www.w3.org/2000/01/rdf-schema#comment> <Analyse one or more known molecular sequences.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.markdup.bam> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0253> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.indel.recal.filter.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#comment> <Analyse a genetic variation, for example to annotate its location, alleles, classification, and effects on individual transcripts predicted for a gene model.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.markdup.bam> <http://www.w3.org/2000/01/rdf-schema#comment> <Predict, recognise and identify positional features in molecular sequences such as key functional sites or regions.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.indel.recal.select.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3227> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.genotyped.vcf.gz.tbi> <http://www.w3.org/2000/01/rdf-schema#comment> <Identify insertion, deletion and duplication events from a sequence alignment.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.recal.combined.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0232> .\n",
      "\t<http://snakemake-provenance/BED/capture.bed> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_0232> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.snv.recal.select.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <http://edamontology.org/operation_3227> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.indel.recal.select.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#comment> <Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/BAM/Sample1.p1.aligned.sam> <http://www.w3.org/2000/01/rdf-schema#comment> <Construct some data entity.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.snv.recal.filter.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#comment> <Filter a set of files or data items according to some property.> .\n",
      "\t<http://snakemake-provenance/VCF/hapcaller.genotyped.vcf.gz> <http://www.w3.org/2000/01/rdf-schema#comment> <Identify insertion, deletion and duplication events from a sequence alignment.> .\n",
      "\t<http://snakemake-provenance/Samples/Sample1/VCF/Sample1.hapcaller.g.vcf> <http://www.w3.org/2000/01/rdf-schema#comment> <Identify and map genomic alterations, including single nucleotide polymorphisms, short indels and structural variants, in a genome sequence.> .\n",
      "}\n",
      "\n",
      ":provenance {\n",
      "    :assertion prov:generatedAtTime \"2021-06-30T23:34:05.697562\"^^xsd:dateTime .\n",
      "    :assertion prov:wasDerivedFrom :experiment .\n",
      "    :assertion prov:wasAttributedTo <https://orcid.org/0000-0002-3597-8557> .\n",
      "}\n",
      "\n",
      ":pubInfo {\n",
      "    ex:pub1 prov:wasAttributedTo <https://orcid.org/0000-0002-3597-8557> .\n",
      "}\n",
      "\n",
      "\n",
      "CPU times: user 28.9 ms, sys: 3.38 ms, total: 32.3 ms\n",
      "Wall time: 31 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "my_ORCID = \"0000-0002-3597-8557\"\n",
    "\n",
    "data_assertions = []\n",
    "\n",
    "np_data_query = \"\"\"\n",
    "    CONSTRUCT {\n",
    "        ?d rdfs:seeAlso ?f .\n",
    "        ?d rdfs:comment ?f_def .\n",
    "    } WHERE {\n",
    "        ?d rdf:type prov:Entity ;\n",
    "           prov:wasGeneratedBy ?x ;\n",
    "           prov:wasAssociatedWith ?tool ;\n",
    "           rdfs:label ?d_label .\n",
    "        \n",
    "        ?tool dc:title ?title ;\n",
    "            biotools:has_function ?f .\n",
    "            \n",
    "        ?f rdfs:label ?f_label ;\n",
    "            oboInOwl:hasDefinition ?f_def .\n",
    "    }\n",
    "\"\"\"\n",
    "\n",
    "results = g.query(np_data_query)\n",
    "for r in results :\n",
    "    data_assertions.append('<'+str(r[0])+'>' \" \" + '<'+str(r[1])+'>' + \" \" + '<'+str(r[2])+'> .')\n",
    "\n",
    "\n",
    "nanopub_template = \"\"\"\n",
    "\n",
    "@prefix : <http://example.org/pub1#> .\n",
    "@prefix ex: <http://example.org/> .\n",
    "@prefix np:  <http://www.nanopub.org/nschema#> .\n",
    "@prefix prov: <http://www.w3.org/ns/prov#> . \n",
    "@prefix xsd:  <http://www.w3.org/2001/XMLSchema#> .\n",
    "\n",
    ":head {\n",
    "    ex:pub1 a np:Nanopublication .\n",
    "    ex:pub1 np:hasAssertion :assertion .\n",
    "    ex:pub1 np:hasProvenance :provenance .\n",
    "    ex:pub1 np:hasPublicationInfo :pubInfo .\n",
    "}\n",
    "\n",
    ":assertion {\n",
    "    $Assertion\n",
    "}\n",
    "\n",
    ":provenance {\n",
    "    :assertion prov:generatedAtTime \\\"\"\"\"+datetime.datetime.now().isoformat()+\"\"\"\\\"^^xsd:dateTime .\n",
    "    :assertion prov:wasDerivedFrom :experiment .\n",
    "    :assertion prov:wasAttributedTo <https://orcid.org/\"\"\"+my_ORCID+\"\"\"> .\n",
    "}\n",
    "\n",
    ":pubInfo {\n",
    "    ex:pub1 prov:wasAttributedTo <https://orcid.org/\"\"\"+my_ORCID+\"\"\"> .\n",
    "}\n",
    "\n",
    "\"\"\"\n",
    "\n",
    "assert_graph = ('\\n\\t').join(data_assertions)\n",
    "\n",
    "np = Template(nanopub_template)\n",
    "np = np.substitute(Assertion = assert_graph)\n",
    "\n",
    "print(np)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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