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eQTL-Catalogue/qtlmap: Usage

Table of contents

General Nextflow info

Nextflow handles job submissions on SLURM or other environments, and supervises running the jobs. Thus the Nextflow process must run until the pipeline is finished. We recommend that you put the process running in the background through screen / tmux or similar tool. Alternatively you can run nextflow within a cluster job submitted your job scheduler.

It is recommended to limit the Nextflow Java virtual machines memory. We recommend adding the following line to your environment (typically in ~/.bashrc or ~./bash_profile):

NXF_OPTS='-Xms1g -Xmx4g'

Running the pipeline

The typical command for running the pipeline is as follows:

nextflow run main.nf -profile tartu_hpc\
   --studyFile testdata/multi_test.tsv\
    --vcf_has_R2_field FALSE\
    --varid_rsid_map_file testdata/varid_rsid_map.tsv.gz\
    --n_batches 25

This will launch the pipeline with the tartu_hpc configuration profile. See below for more information about profiles.

Note that the pipeline will create the following files in your working directory:

work            # Directory containing the nextflow working files
results         # Finished results (configurable, see below)
.nextflow_log   # Log file from Nextflow
# Other nextflow hidden files, eg. history of pipeline runs and old logs.

The most up-to-date usage information can be viewed with:

nextflow run main.nf --help

Nextflow itself depends on Java and tartu_hpc configuration profile further requires that Singularity is available in PATH. At the University of Tartu HPC, these can be loaded using:

module load java-1.8.0_40
module load singularity/3.5.3

Main arguments

Mandatory Arguments

--studyFile

Use this to specify the location of the text file describing the locations of all required input files. Multiple rows of the studyFile can be used to run the qtlmap pipeline across many different cell types, conditions or phenotype types (gene expression, transcript usage, etc). The required columns of the studyFile are:

  1. qtl_subset - unique identifer for the QTL analysis (e.g. name of the cell type, tissue or quantification method or any other parameter that is used to partition the data.
  2. count_matrix - normalised phenotype matrix. The name of the first column should be phenotype_id, other columns should correspond to sample_ids.
  3. pheno_meta - specifies the location of your phenotype metadata file (.tsv). Should contain at least the following columns: phenotype_id, chromosome, phenotype_pos, strand. The phenotype_pos column is used to define the cis window around each phenotype.
  4. sample_meta - specifies the location of your sample metadata file (.tsv). Should contain at least the following columns: sample_id, genotype_id, qtl_group
  5. vcf - Genotype file used for QTL analysis. Sample ids of the VCF file should match the genotype_id column in the sample_meta file.
  6. tpm_file - specifies the median TPM value of each phenotype in each qtl_group (from sample_meta file). These TPM values are not used in QTL analysis and are only merged into final summary statistics file as gene annotations. If the tpm_file is not available, then this can be replaced by a dummy placeholder value 'null.txt'.

See the section about input files for more details how the columns in different files related to each other. Example studyFile is available here and example input data can be seen here.

Note that qtlmap uses the intersection of samples present in count_matrix and sample_meta for analysis. This means that if you wish to perform analysis only on a subset of the samples (e.g. females) then it is sufficient to filter the sample_meta file leaving the count_matrix unchanged.

nextflow run main.nf --studyFile testdata/multi_test.tsv
params {
    genotype_vcf = "$baseDir/testdata/multi_test.tsv"
}

Optional Arguments

--cis_window

Use this to specify the cis-window length in bases. Deafult value is 1,000,000 bases (1Mb)

nextflow run main.nf [mandatory arguments here] --cis_window 1500000
params {
    cis_window = 1500000
}

--mincisvariant

Use this to specify the threshold minimum variants in specified cis window. If for specific phenotype, there are less variants found in cis window than this threshold, the phenotype is filtered out and not processed further. Default value is 5

nextflow run main.nf [mandatory arguments here] --mincisvariant 10
params {
    mincisvariant = 10
}

--n_batches

Use this to specify the number of batches used in QTL mapping run. FastQTL/QTLTools will split the genome into this number of chunks and perform the run in a parallel manner. The default value is 400. The number of batches has to exceed the number of chromosomes in the VCF file.

nextflow run main.nf [mandatory arguments here] --n_batches 200
params {
    n_batches = 200
}

--is_imputed

Use this to specify if the provided genotype (VCF) file is imputed or not. The imputed genotype files should have the following columns CHROM, POS, ID, REF, ALT, TYPE, AC, AN, MAF, R2. The default value is TRUE

nextflow run main.nf [mandatory arguments here] --is_imputed FALSE
params {
    is_imputed = false
}

Using profiles

-profile

Use this parameter to choose a configuration profile. Profiles can give configuration presets for different compute environments. Note that multiple profiles can be loaded, for example: -profile docker - the order of arguments is important!

If -profile is not specified at all the pipeline will be run locally and expects all software to be installed and available on the PATH.

  • awsbatch
    • A generic configuration profile to be used with AWS Batch.
  • conda
    • A generic configuration profile to be used with conda
    • Pulls most software from Bioconda
  • docker
    • A generic configuration profile to be used with Docker
    • Pulls software from dockerhub: nfcore/qtlmap
  • singularity
    • A generic configuration profile to be used with Singularity
    • Pulls software from singularity-hub
  • test
    • A profile with a complete configuration for automated testing
    • Includes links to test data so needs no other parameters

Job resources

Automatic resubmission

Each step in the pipeline has a default set of requirements for number of CPUs, memory and time. For most of the steps in the pipeline, if the job exits with an error code of 143 (exceeded requested resources) it will automatically resubmit with higher requests (2 x original, then 3 x original). If it still fails after three times then the pipeline is stopped.

Custom resource requests

Wherever process-specific requirements are set in the pipeline, the default value can be changed by creating a custom config file. See the files hosted at nf-core/configs for examples.

If you are likely to be running nf-core pipelines regularly it may be a good idea to request that your custom config file is uploaded to the nf-core/configs git repository. Before you do this please can you test that the config file works with your pipeline of choice using the -c parameter (see definition below). You can then create a pull request to the nf-core/configs repository with the addition of your config file, associated documentation file (see examples in nf-core/configs/docs), and amending nfcore_custom.config to include your custom profile.

If you have any questions or issues please send us a message on Slack.

AWS Batch specific parameters

Running the pipeline on AWS Batch requires a couple of specific parameters to be set according to your AWS Batch configuration. Please use the -awsbatch profile and then specify all of the following parameters.

--awsqueue

The JobQueue that you intend to use on AWS Batch.

--awsregion

The AWS region to run your job in. Default is set to eu-west-1 but can be adjusted to your needs.

Please make sure to also set the -w/--work-dir and --outdir parameters to a S3 storage bucket of your choice - you'll get an error message notifying you if you didn't.

Other command line parameters

--outdir

The output directory where the results will be saved.

--email

Set this parameter to your e-mail address to get a summary e-mail with details of the run sent to you when the workflow exits. If set in your user config file (~/.nextflow/config) then you don't need to speicfy this on the command line for every run.

-name

Name for the pipeline run. If not specified, Nextflow will automatically generate a random mnemonic.

This is used in the MultiQC report (if not default) and in the summary HTML / e-mail (always).

NB: Single hyphen (core Nextflow option)

-resume

Specify this when restarting a pipeline. Nextflow will used cached results from any pipeline steps where the inputs are the same, continuing from where it got to previously.

You can also supply a run name to resume a specific run: -resume [run-name]. Use the nextflow log command to show previous run names.

NB: Single hyphen (core Nextflow option)

-c

Specify the path to a specific config file (this is a core NextFlow command).

NB: Single hyphen (core Nextflow option)

Note - you can use this to override pipeline defaults.

--custom_config_version

Provide git commit id for custom Institutional configs hosted at nf-core/configs. This was implemented for reproducibility purposes. Default is set to master.

## Download and use config file with following git commid id
--custom_config_version d52db660777c4bf36546ddb188ec530c3ada1b96

--max_memory

Use to set a top-limit for the default memory requirement for each process. Should be a string in the format integer-unit. eg. --max_memory '8.GB'

--max_time

Use to set a top-limit for the default time requirement for each process. Should be a string in the format integer-unit. eg. --max_time '2.h'

--max_cpus

Use to set a top-limit for the default CPU requirement for each process. Should be a string in the format integer-unit. eg. --max_cpus 1

--plaintext_email

Set to receive plain-text e-mails instead of HTML formatted.