In this session, we are going to construct polygenic risk score using PRS-CS.
References : PRS-CS github, PRS-CS paper.
The data we are going to use are already preprocessed or downloaded.
ssh leelabguest@147.47.200.131 -p 22555
ssh leelabsg[01-07]
conda activate python_3
python /data/home/leelabguest/PRS_tutorial/PRScs/PRScs.py \
--ref_dir=/media/leelabsg-storage0/PRS_tutorial/data/reference/ldblk_1kg_eas \
--bim_prefix=/media/leelabsg-storage0/PRS_tutorial/data/plink/sample \
--sst_file=/media/leelabsg-storage0/PRS_tutorial/data/summary_stat/sumstats_prscs.txt \
--n_gwas=177415 \
--out_dir=/data/home/leelabguest/PRS_tutorial/YOUR_DIRECTORY/PRScs
for i in {1..22}; do cat "/data/home/leelabguest/PRS_tutorial/YOUR_DIRECTORY/PRScs_pst_eff_a1_b0.5_phiauto_chr$i.txt" >> /data/home/leelabguest/PRS_tutorial/YOUR_DIRECTORY/prscs_chr1-22.txt; done
/data/home/leelabguest/plink \
--bfile /media/leelabsg-storage0/PRS_tutorial/data/plink/sample \
--score /data/home/leelabguest/PRS_tutorial/YOUR_DIRECTORY/prscs_chr1-22.txt 2 4 6 \
--out /data/home/leelabguest/PRS_tutorial/YOUR_DIRECTORY/score
cat /data/home/leelabguest/PRS_tutorial/YOUR_DIRECTORY/score.profile