ImmunoTyper-SR is a powerful tool for Immunoglobulin Variable Gene genotyping and CNV analysis from whole genome sequencing (WGS) short reads using ILP Optimization. Check out our paper here for more details.
📢 New Feature:
<prefix>-<gene_type>-novel-variants.txt
and phased VCFs are available in <prefix>-<gene_type>-novel_variant_vcfs/<gene_id>_variants.vcf
.ImmunoTyper-SR leverages the Gurobi solver for optimization. You need a valid license to use Gurobi. Licenses are free for academic purposes.
For the easiest installation, we recommend using the Docker image available on DockerHub at cdslsahinalp/immunotyper-sr
.
To run the image with Singularity (commonly used on HPCs), use the following command:
singularity pull docker://cdslsahinalp/immunotyper-sr
singularity run -B <GUROBI_LICENSE_PATH>:/opt/gurobi/gurobi.lic -B <BAM_DIRECTORY>:<BAM_DIRECTORY> -B <OUTPUT_PATH>:/output immunotyper-sr_latest.sif <OPTIONAL ARGUMENTS> <BAM_DIRECTORY>/<BAM_FILE>
You can find your gurobi license file path with echo $GRB_LICENSE_FILE
.
If you already have BWA installed and prefer not to create a new environment, you can download the latest release binary (see right toolbar) and install it with pip:
pip install <binary.whl>
For the best experience, we recommend setting up a clean environment first:
conda create -n immunotyper-SR -c bioconda python=3.8 bwa samtools
conda activate immunotyper-SR
pip install <binary.whl>
Installing ImmunoTyper-SR with pip will automatically install these dependencies:
In addition to the above, you will need
conda create -n immunotyper-SR -c bioconda python=3.8 bwa samtools
conda activate immunotyper-SR
pip install <binary.whl>
To check that gurobi is correctly configured, run gurobi_cl
from a shell.
If the binary fails to install, you can build the tool from source:
conda create -n immunotyper-SR -c bioconda python=3.8 bwa samtools
conda activate immunotyper-SR
git clone git@github.com:algo-cancer/ImmunoTyper-SR.git ./ImmunoTyper-SR
cd ImmunoTyper-SR
python -m pip install --upgrade build
python -m build
pip install dist/<.tar.gz or .whl build>
After installing with pip, use the command immunotyper-SR. The only required input is a BAM file. Outputs are generated in the current working directory, where
IMPORTANT: If your BAM was mapped to GRCh37 use the --hg37
flag.
$ immunotyper-SR --help
usage: immunotyper-SR [-h] [--gene_type {ighv,iglv,trav,igkv,trbv,trdv,trgv}] [--output_dir OUTPUT_DIR] [--ref REF] [--hg37] [--solver {gurobi}] [--bwa BWA] [--max_copy MAX_COPY] [--landmarks_per_group LANDMARKS_PER_GROUP] [--landmark_groups LANDMARK_GROUPS] [--stdev_coeff STDEV_COEFF] [--seq_error_rate SEQ_ERROR_RATE] [--solver_time_limit SOLVER_TIME_LIMIT]
[--debug_log_path DEBUG_LOG_PATH] [--write_cache_path WRITE_CACHE_PATH] [--threads THREADS] [--no_coverage_estimation]
bam_path
ImmunoTyper-SR: Ig Genotyping using Short Read WGS
positional arguments:
bam_path Input BAM file
optional arguments:
-h, --help show this help message and exit
--gene_type {ighv,iglv,trav,igkv,trbv,trdv,trgv}
Specify which genes to target
--output_dir OUTPUT_DIR
Path to output directory. Outputs txt file of allele calls with prefix matching input BAM file name.
--ref REF Path to the reference FASTA to decode CRAM files. Option is not used if bam_path is not a CRAM.
--hg37 Flag if BAM mapped to GRCh37 not GRCh38
--solver {gurobi} Choose ilp solver
--bwa BWA path to bwa executible if not in $PATH
--max_copy MAX_COPY Maximum number of allele copies to call
--landmarks_per_group LANDMARKS_PER_GROUP
Number of landmarks per group to use (default = 6)
--landmark_groups LANDMARK_GROUPS
Number of landmark groups to use (default = 6)
--stdev_coeff STDEV_COEFF
Standard deviation scaling coefficient (default = 1.5)
--seq_error_rate SEQ_ERROR_RATE
Expected sequence error rate (default = 0.02)
--solver_time_limit SOLVER_TIME_LIMIT
Time limit for ILP solver in hours
--debug_log_path DEBUG_LOG_PATH
Path to write log
--write_cache_path WRITE_CACHE_PATH
Specific location and name of allele db sam mapping cache
--threads THREADS Max number of threads to use
--no_coverage_estimation