Last updated: 2020-09-10
Checks: 2 0
Knit directory: PSYMETAB/
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These are the previous versions of the R Markdown and HTML files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view them.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| html | 4b99157 | Jenny Sjaarda | 2020-09-10 | Build site. |
| Rmd | 299e192 | Jenny Sjaarda | 2020-09-10 | adding instructions for extracting genetic data |
| html | d53b378 | Jenny Sjaarda | 2020-09-08 | Build site. |
| Rmd | 8743745 | Jenny Sjaarda | 2020-09-08 | wflow_publish(“analysis/extract_genetic_data.Rmd”) |
The following document outlines the procedure to extract genetic data located on the HPC1 servers.
${snp_list}).HPC1 server via filezilla:
hpc1.chuv.chje4649LacLeman202022/data/sgg2/jenny/projects/PSYMETAB/data/raw/extractions/data/sgg2/jenny/projects/PSYMETAB/data/raw/extractions/${requester}./data/sgg2/jenny/projects/PSYMETAB/code/extractions (for e.g. /data/sgg2/jenny/projects/PSYMETAB/code/extractions/Aurelie.sh)/data/sgg2/jenny/projects/PSYMETAB/code/extractions/${requester}.sh.Nicolas_extract.sh script as the new one will be nearly identical.job-name, (2) folder input, (3) folder ouput, (4) comment at end of file indicating how to launch the script.HPC1 using PUTTY:
je4649@hpc1.chuv.chLacLeman2020sbatch $projects/PSYMETAB/code/extractions/${requester}_extract.sh (this assumes projects is defined as /data/sgg2/jenny/projects, if not replace $projects with explicit path or define projects before hand, if logged in as je4649, project is automatically defined)./data/sgg2/jenny/projects/PSYMETAB/data/processed/extractions/${resquester}/${snp_list}.${snp_list}_rsids.txt: list of rsIDs with empty characters removed (in most cases this should be identical to the input file from #1).${snp_list}_SNP_info.txt: info file for each rsID, extracted from HRC list (see HRC website), columns correspond to: #CHROM POS ID REF ALT AC AN AF AC_EXCLUDING_1000G AN_EXCLUDING_1000G AF_EXCLUDING_1000G AA.$chr), extracted from imputed data, there are the following files from extracting the chromosome specific genetic data using PLINK:
${snp_list}_chr${chr}.txt: list of rsIDs on chr${chr}${snp_list}_chr${chr}.psam${snp_list}_chr${chr}.pvar${snp_list}_chr${chr}.pgen${snp_list}_chr${chr}.pgen${snp_list}_chr${chr}.raw${snp_list}_chr${chr}.log${snp_list}_extraction.txt: merged genetic data from imputed files.${snp_list}_missing_snps.txt: list of SNPs that were not extracted from imputed files (if this file is empty, all SNPs were in imputed data set).${snp_list}_missing_snps_extract.fam: PLINK extraction from original genotype data.${snp_list}_missing_snps_extract.bim: PLINK extraction from original genotype data.${snp_list}_missing_snps_extract.bed: PLINK extraction from original genotype data.${snp_list}_missing_snps_extract.raw: PLINK extraction from original genotype data.${snp_list}_missing_snps_extract.log: PLINK extraction from original genotype data.${snp_list}_extraction_geno.txt: merged genetic data, same file as above, but with additional SNPs extracted from original genotype data, this is the main results file:
GPCR ID.CEU samples as this our largest and cleanest sample. If using only European, adjust for at least the first 10 PCs in your analysis. If you need to include additional ethnic groups, you have two options: (1) analyze each ethnic group seperately, adjusting for PCs or (2) analyze the entire group together without PCs (PCs were calculated in each ethnic group seperately so you cannot include them in a model where all ethnic groups are included).${snp_list}_missing_geno_snps.txt: list of SNPs that are still missing after extracting SNPs from original genotyped data.
${snp_list}_missing_snps_extract.bim.${snp_list}_extraction_geno.txt) to a CHUV computer via filezilla.