bNAb-ReP

An Automated Pipeline for HIV-1 Resistance Prediction to 33 Neutralizing Antibodies

Installation

bNAb-ReP has been successfully tested on Linux systems

Environment

• Download and install conda environment for 64-bit linux or Mac (https://conda.io/miniconda.html) using Python 3.7

  • Install in command line: ./Miniconda3-latest-Linux-x86_64.sh (Linux)
  • Open a new terminal window or source your bash with: source ~/.bashrc

• Create bNAb-ReP environment in command line: conda create --name bNAb-ReP

• Activate bNAb-ReP environment in command line: conda activate bNAb-ReP

• Install require packages by running the following in command line:

  • conda install -c r r
  • conda install -c bioconda r-bio3d
  • conda install -c r r-rcurl
  • conda install -c r r-jsonlite
  • conda install -c cidermole jdk8 (Linux) or conda install -c cyclus java-jdk (Mac)
  • conda install -c bioconda mafft
  • conda install -c r r-data.table
  • conda install -c r r-foreach
  • conda install -c r r-doparallel
  • conda install -c r r-rocr
  • conda install -c conda-forge r-geosphere
  • conda install -c conda-forge readline

• Install R library h2o (version 3.16.0.2) (https://cran.r-project.org/web/packages/h2o/index.html) (see "Old sources") manually by:

  The following two commands remove any previously installed H2O packages for R.

  if ("package:h2o" %in% search()) { detach("package:h2o", unload=TRUE) }

  if ("h2o" %in% rownames(installed.packages())) { remove.packages("h2o") }

  Next, we download packages that H2O depends on.

  pkgs <- c("RCurl","jsonlite")

  for (pkg in pkgs) { if (! (pkg %in% rownames(installed.packages()))) { install.packages(pkg) } }

  Now we download, install and initialize the H2O package for R.

  install.packages("h2o", type="source", repos="https://h2o-release.s3.amazonaws.com/h2o/rel-wheeler/2/R")

  Finally, let's load H2O and start up an H2O cluster

  library(h2o)

  h2o.init()

Run

bNAb-ReP can be run in the command line

4 input arguments are necessary to run the bNAb-ReP

1. bNAb, choose one of 33 bNAbs (10-1074, 2F5, 2G12, 35O22, 3BNC117, 4E10, 8ANC195, CH01, DH270.1, DH270.5, DH270.6, HJ16, NIH45-46, PG16, PG9, PGDM1400, PGT121, PGT128, PGT135, PGT145, PGT151, VRC-CH31, VRC-PG04, VRC01, VRC03, VRC07, VRC13, VRC26.08, VRC26.25, VRC29.03, VRC34.01, VRC38.01, b12)
2. HIV-1 Env sequence(s) in FASTA format (https://en.wikipedia.org/wiki/FASTA_format). (Please use ".fasta" for file name extension)
3. Path to installed MAFFT software (e.g. "/usr/local/bin/mafft")
4. Output prefix (e.g. "OUTPUT")

Dependencies

1. Please download directories alignments and models
2. Copy directories alignments and models in the current path, where you are intending to execute the script

Execute in the command line

R --vanilla < run_bNAb-ReP_v1.1-4.R VRC01 testing.fasta mafft OUTPUT

Result

Results will be saved in OUTPUT_probabilities.txt. For each sequence in the input alignment file a probability value between 0-1 is calculated, with higher values corresponding to neutralization sensitivity.

Example/Test

HXB2 and BG505 testing sequences

R --vanilla < run_bNAb-ReP_v1.1-4.R VRC01 testing.fasta mafft OUTPUT

Contact

Reda Rawi: [email protected]