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Clair: Exploring the limit of using deep neural network on pileup data for germline variant calling

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Installation

# make sure channels are added in conda
conda config --add channels defaults
conda config --add channels bioconda
conda config --add channels conda-forge

# create conda environment named "clair-env"
conda create -n clair-env -c bioconda clair
conda activate clair-env
conda install deepdish

# store clair.py PATH into $CLAIR variable
CLAIR=`which clair.py`

# run clair like this afterwards
python $CLAIR --help

The conda environment has the Pypy3 interpreter installed, but one Pypy3 package intervaltree is still missing. The reason why this is not installed by default is because this is not yet available in any conda repositories. To install the package for Pypy3, after activating the conda environment, please run the following commands:

pypy3 -m ensurepip
pypy3 -m pip install --no-cache-dir intervaltree==3.0.2

Create dataset

python3 clair.py callVarBam --chkpnt_fn ./model --bam_fn <chr.bam.bai> --ref_fn <chr20.fa>  --call_fn .chr20.vcf --pysam_for_all_indel_bases --threads 1 --qual 100 --ctgName chr20 --ctgStart 10269870 --ctgEnd 46672937 --pipe_line --store_loaded_mini_match

Run command

Run command

# download models
wget http://www.bio8.cs.hku.hk/clair_models/illumina/12345.tar
tar -xf 12345.tar
python3 my_prediction.py --chkpnt_fn ./model --sampleName HG001 --threads 1 --qual 100 --input_fn <prediction_input.h5> --output_fn <prediction_output.h5>

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Clair: Exploring the limit of using deep neural network on pileup data for germline variant calling

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