Difference between revisions of "GSCAN dbGaP"
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===Phenotypes=== | ===Phenotypes=== | ||
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===Genotypes=== | ===Genotypes=== | ||
Revision as of 18:34, 6 September 2016
Studies
Framingham
ID Mapping
The following snppit describes how the PLINK genotype file IDs (which use "sampid") were mapped to the dbGaP_Subject_ID contained in the available phenotype files. The snippet only contains one of Joyce Ling's phenotype files for illustration only.
This script and the results it produces can be found in /work/KellerLab/GSCAN/dbGaP/Framingham/ID_mapping.r
### ID mapping file from dbGaP_Subject_ID to SAMPID
ID.map <- read.table(gzfile("/work/KellerLab/GSCAN/dbGaP/Framingham/PhenoGenotypeFiles/RootStudyConsentSet_phs000007.Framingham.v28.p10.c1.HMB-IRB-MDS/PhenotypeFiles/phs000007.v28.pht001415.v16.p10.Framingham_Sample.MULTI.txt.gz"), header=T, sep="\t", stringsAsFactors=F)
### Genotype files
genotype.IDs <- read.table("/work/KellerLab/GSCAN/dbGaP/Framingham/PhenoGenotypeFiles/ChildStudyConsentSet_phs000342.Framingham.v16.p10.c1.HMB-IRB-MDS/GenotypeFiles/phg000006.v9.FHS_SHARe_Affy500K.genotype-calls-matrixfmt.c1/subject_level_PLINK_sets/FHS_SHARe_Affy500K_subjects_c1.fam", header=F)
names(genotype.IDs) <- c("famid", "SAMPID", "patid", "matid", "sex", "phenotype")
length(which(genotype.IDs$SAMPID %in% ID.map$SAMPID))
## 6954
x <- merge(genotype.IDs, ID.map, by="SAMPID", all.x=T)
x <- x[,c(1:5,7)]
### One of Joyce's phenotype ID files (eventually all phenotypes for all available participants were merged in, but this is a good example.)
phenotypes <- read.table("OffC_Exam_1.txt", header=T, sep="\t")
xx <- merge(x, phenotypes, by="dbGaP_Subject_ID", all=TRUE)
xx <- xx[,c(2:ncol(xx),1)] ## Reorder so the dbGaP_Subject_ID is the last column
write.table(xx, file="framingham_GSCAN_phenotypesCovariates.ped", quote=FALSE, sep="\t", row.names=F)
Phenotypes
(Joyce will update this section)
Genotypes
We used the Affy 500K genotypes found here: /work/KellerLab/GSCAN/dbGaP/Framingham/PhenoGenotypeFiles/ChildStudyConsentSet_phs000342.Framingham.v16.p10.c1.HMB-IRB-MDS/GenotypeFiles/phg000006.v9.FHS_SHARe_Affy500K.genotype-calls-matrixfmt.c1/subject_level_PLINK_sets/FHS_SHARe_Affy500K_subjects_c1.[bed|bim|fam]
ARIC
(Hannah/Joyce to update this section following Framingham as a guide)
ID Mapping
Phenotypes
Genotypes
MESA
(Hannah/Joyce to update following Framingham as a guide)
Phenotypes
Description of phenotypes can be found here: Media:MESA phenotypes - FINAL.pdf
eMERGE
(Hannah/Joyce to update following Framingham as a guide)
Phenotypes
Description of phenotypes can be found here: Media:EMERGE.pdf
Stroke
(Hannah/Joyce to update following Framingham as a guide)
Genotype Processing
Pre-Phasing QC
QC parameters that we chose: MAF > 0.01
SNP callrate > 0.95
Missingness per individual > 0.95
HWE = 0.05 / number of markers but greater than 5e-8
To update the strand builds: http://www.well.ox.ac.uk/~wrayner/strand/
## Check strands against latest 1000G: http://www.well.ox.ac.uk/~wrayner/tools/ #!/bin/bash #SBATCH --qos=blanca-ibg #SBATCH --mem=40gb perl HRC-1000G-check-bim.pl -b ARIC_b37_filtered.bim -f ARIC_b37_filtered.frq -r 1000GP_Phase3_combined.legend -g -p EUR
## Phasing using shapeit
#!/bin/bash
#SBATCH --mem=20gb
#SBATCH --time=48:00:00
#SBATCH -o shapeit_aric_%j.out
#SBATCH -e shapeit_aric_%j.err
#SBATCH --qos blanca-ibgc1
#SBATCH --ntasks-per-node 48
#SBATCH -J shapeit_aric
shapeit -B ARIC_b37_filtered-updated-chr${1} -M /rc_scratch/meli7712/dbGAP/1000GP_Phase3/genetic_map_chr${1}_combined_b37.txt -O phased/ARIC_b37_filtered-updated-chr${1}.phased -T 48
## To convert the shapeit output into vcf
#!/bin/bash
#SBATCH --mem=20gb
#SBATCH --time=24:00:00
#SBATCH -o shapeit_mesa_%j.out
#SBATCH -e shapeit_mesa_%j.err
#SBATCH --qos janus
#SBATCH --ntasks-per-node 12
#SBATCH -J shapeit_mesa
shapeit -convert --input-haps mesa-chr${1}.phased --output-vcf mesa-chr${1}.phased.vcf -T 12
## Imputation
#!/bin/bash
#SBATCH --mem=30gb
#SBATCH --time=72:00:00
#SBATCH -o impute_mesa_%j.out
#SBATCH -e impute_mesa_%j.err
#SBATCH --qos blanca-ibgc1
#SBATCH --ntasks-per-node 48
#SBATCH -J impute_mesa
/work/KellerLab/Zhen/bin/Minimac3/bin/Minimac3 --haps mesa-chr${1}.phased.vcf --cpus 48 --refHaps /rc_scratch/meli7712/dbGAP/references/${1}.1000g.Phase3.v5.With.Parameter.Estimates.m3vcf.gz --chr ${1} --noPhoneHome --format GT,DS,GP --allTypedSites --prefix mesa-chr${1}.phased.imputed