B-MyRepCLL

pipeline for a consensus-oriented analysis of B-cell clones

The strategy is mapping reads separately against the different IMGT gene segments references, and following a clone-centered determination, achieved with the obtention of a consensus sequence. B-cell rearrangements are defined after IGHV-IGHJ correspondence determination and a specific procedure has been designed to cope with unspecific mapping and gene-call primer biases, and the calculation of the clonal fraction the unique profile of each patient.

The first module, src/pipeline.py, annotates VDJ calls and mutational status for all the IGHV alleles found per patient. The second module, src/onlyclonality.py, generates filtering steps for the minimization of artifacts and outputs homology_resume*.xlsx with the final results, with a calculation of the clonal and subclonal fraction on each sample.

For installation, first clone the repository.

You can install all the dependencies directly using conda:

conda env create -f environment.yml

if not, install the following requirements manually:

Requirements

bwa 0.7.15 or above
bamtools 2.4 or above
bcftools 1.7 or above
bedtools 2.26 or above
bbduk(bbtools), repair(bbtools) BBMap version 38 or above
emboss water 6.6.0 or above
samtools 1.7 or above
freebayes 1.1.0 or above
seqtk 1.2 or above
Python
R

PIP Install Requirements

## Python 2
pip install -r requirements.txt 
## or Python 3
pip3 install -r requirements.txt

Recommended arguments (default workflow validated with CLL data)

python B-MyRepCLL/src/pipeline.py --pipeline -f $fastqfilesFolder -o $outputDir -v -p$nproc --basal --primers $FASTAfileVHprimers --cdr3s > log.log

Automatic execution of the pipeline with default validated parameters, final summary files and quality control

python B-MyRepCLL/launch-default.py $fastqfilesFolder $coverage_threshold $outputDir

This mode has requirements of other repositories: https://github.com/afuentri/QC

Publication in process