Polygenic risk score with bilevel continuous shrinkage for incorporating functional annotations.
- Download/Clone PRSbils (this repository) to your local machine
- Install required python packages:
pip3 install -r requirements.txt
- Get the input files ready
- Download and extract LD reference panel from 1000 Genomes Project phase 3 (the same procedure as in PRSCS):
- Genotype file
- GWAS summary statistics
- Mapping file from SNPs to annotation groups
- Run
PRSbils.py
to get the trained weights for SNPs with different functional annotations.
You can test the program using the following bash command after downloading the 1000G European LD referenfce panel file under the home directory:
pip3 install -r requirements.txt
python3 PRSbils.py \
--ref_dir=./1000G/ldblk_1kg_eur \
--bim_prefix=./data/genotypes_plink_chr1_train \
--sst_file=./data/sumstat.txt \
--map_file=./data/snpmap.txt \
--n_gwas=50000 \
--out_dir=./data/output_trained_weights_prsbils \
--chrom=1 \
--n_iter=1000 \
--thres=1e-04 \
--beta_std=False \
--flip=True
The output file is ./data/output_trained_weights_prsbils_beta_chr1.txt
, which is a tab-delimited text file with the following columns:
[Chromosome] [SNP ID] [SNP Position] [Allele 1] [Allele 2] [Weight in the summary statistics file] [Weight from PRSbils] [Annotation Group] [Subgroup (not yet implemented)] [Allele Frequency]
Please check the next section or run python3 PRSbils.py --help
for details about the parameters.
usage: PRSbils.py [-h] --ref_dir REF_DIR --bim_prefix BIM_PREFIX --sst_file
SST_FILE --map_file MAP_FILE [--map_gcol MAP_GCOL] --n_gwas
N_GWAS --out_dir OUT_DIR [--a A] [--b B] [--c C] [--d D]
[--e E] [--f F] [--n_iter N_ITER]
[--chrom CHROM [CHROM ...]] [--beta_std [BETA_STD]]
[--thres THRES] [--ignore_blk [IGNORE_BLK]]
[--verbose [VERBOSE]] [--fixtau [FIXTAU]] [--flip [FLIP]]
PRSbils: Polygenic Risk Score with Bilevel Continuous Shrinkage
optional arguments:
-h, --help show this help message and exit
--ref_dir REF_DIR Full path (including folder name) to the directory
(ldblk_1kg_eur, ldblk_1kg_eas or ldblk_1kg_afr) that
contains information on the LD reference panel
(snpinfo_1kg_hm3 and ldblk_1kg_chr*.hdf5)
--bim_prefix BIM_PREFIX
Full path and the prefix of the bim file
--sst_file SST_FILE Full path and the file name of the GWAS summary
statistics Summary statistics file must be tab
delimited with the following format (including the
header line): SNP A1 A2 BETA P Or: SNP A1 A2 OR P
--map_file MAP_FILE Full path and the file name of the mapping file from
SNPs to sets. Map file must have the MSigDB file
format : [CHROM] [SNPID] [SETNAME] [GROUP (optional)]
--map_gcol MAP_GCOL (Not yet implemented) Column id for group info in map_file. Default is None
(no group information)
--n_gwas N_GWAS Sample size of the GWAS
--out_dir OUT_DIR Output directory and output filename prefix of the
posterior effect size estimates
--a A Parameter a for sigma. Default is 0.001
--b B Parameter b in the gamma prior for sigma. Default is
0.001
--c C Parameter c for group implementation. Default is 0.001
--d D Parameter d for group implementation. Default is 0.001
--e E Parameter e for lambda. Default is 1
--f F Parameter f for lambda. Default is 0.5
--n_iter N_ITER Number of maximum iterations. Default is 1000
--chrom CHROM [CHROM ...]
The chromosome on which the model is fitted. Default
is iterating through 22 autosomes
--beta_std [BETA_STD]
Boolean. If True, return standardized posterior SNP
effect sizes. Default is False
--thres THRES Threshold value for convergence. Default is 0.001
--ignore_blk [IGNORE_BLK]
Boolean. If false, elements categorized as same set
but in different ld will be treated as different sets.
Default is False
--verbose [VERBOSE] Boolean. Default is False
--fixtau [FIXTAU] Boolean. If false, will estimate tau in algorithm,
otherwise will fix at 1. Default is False
--flip [FLIP] Boolean. If false, signs of beta in summary statistics
will not be flipped when there's a switch in A1 and A2
alleles. Default is False