bam2tensor

Toolbox to convert BAM files into tensors

Installation

Download this repository, go to the directory it resides and run:

git clone https://github.com/TRON-Bioinformatics/bam2tensor.git
cd bam2tensor
pip install -e .

Requirements

• Python 3.9+
• Packages listed under environment.yml
• The required libraries can be found under setup.cfg and are automatically installed when you install this package as shown above.

Running the nextflow pipeline

Usage:

    nextflow run tron-bioinformatics/bam2tensor
    -profile conda \
    --input_files input_files \
    --publish_dir out_dir \
    --reference genome_ref.fa \
    --window 150 \
    --max_coverage 500 \
    --read_length 50 \
    --max_mapq 60 \
    --max_baseq 82

Input:

• input_files: the path to a tab-separated values file containing in each row the sample name and a BAM file

  The input file does not have a header!

  Example input file:

  name1 tumor_bam1 tumor_bai1 normal_bam1 normal_bai1 candidates1.tsv

  name2 tumor_bam2 tumor_bai2 normal_bam2 normal_bai2 candidates2.tsv

• reference: the reference genome

• window: length of the window to be included around the variant

• max_coverage: Maximum coverage value to normalize coverage matrices

• read_length: The length of majority of the reads in BAM

• max_mapq: Maximum mapping quality to normalize mapping quality matrices, values indicating unknown mapping quality is ignored

• max_baseq: Maximum base quality to normalize base quality matrices, values indicating unknown base quality is ignored

Optional input:

• publish_dir: the folder where to publish output

• memory: the ammount of memory used by each job (default: 15g)

• cpus: the number of CPUs used by each job (default: 8)

Output:

• Tensors under the output folder