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@147.47.200.192
launch-shell 0 720 leelabsg
conda activate python3
mkdir /home/n1/leelabguest/GCDA/usr/YOUR_DIRECTORY/practice_3
python /home/n1/leelabguest/GCDA/3_PRS/PRScs/PRScs.py \
--ref_dir=/home/n1/leelabguest/GCDA/3_PRS/data/reference/ldblk_1kg_eas \
--bim_prefix=/home/n1/leelabguest/GCDA/3_PRS/data/plink/sample \
--sst_file=/home/n1/leelabguest/GCDA/3_PRS/data/summary_stat/sumstats.txt \
--n_gwas=177618 \
--out_dir=/home/n1/leelabguest/GCDA/usr/YOUR_DIRECTORY/practice_3/prscs
for i in {1..22}; do cat "/home/n1/leelabguest/GCDA/usr/YOUR_DIRECTORY/practice_3/prscs_pst_eff_a1_b0.5_phiauto_chr$i.txt" >> /home/n1/leelabguest/GCDA/usr/YOUR_DIRECTORY/practice_3/prscs_chr1-22.txt; done
/home/n1/leelabguest/plink \
--bfile /home/n1/leelabguest/GCDA/3_PRS/data/plink/sample \
--score /home/n1/leelabguest/GCDA/usr/YOUR_DIRECTORY/practice_3/prscs_chr1-22.txt 2 4 6 \
--out /home/n1/leelabguest/GCDA/usr/YOUR_DIRECTORY/practice_3/score