Last updated: 2020-10-16
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Knit directory: NRCRI_2020GS/
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DArTseqLD (DCas20-5510) contains new NRCRI GS C3.
Impute with RefPanelWA (W. Africa RefPanel)
Copy the imputation reference panel from 2019 to the data/ folder.
#cp -r /home/jj332_cas/marnin/NRCRI_2020GS /workdir/mw489/
cp -r /home/jj332_cas/marnin/NRCRI_2020GS/data/Report-DCas20-5510 /workdir/mw489/NRCRI_2020GS/data/
#cp -r /home/jj332_cas/CassavaGenotypeData/CassavaGeneticMap /workdir/mw489/NRCRI_2020GS/data/
#cp /home/jj332_cas/CassavaGenotypeData/nextgenImputation2019/ImputationStageII_71219/chr*_ImputationReferencePanel_StageIIpartI_72219.vcf.gz /workdir/mw489/NRCRI_2020GS/data/Impute with Beagle V5.0.
Use the “imputation reference panel” dataset from 2019, e.g. chr1_ImputationReferencePanel_StageIIpartI_72219.vcf.gz as reference.
Used 1 large memory Cornell CBSU machine (e.g. cbsulm16; 112 cores, 512 GB RAM), running 1 chromosome at a time.
R functions are stored in the code/ sub-directory. Functions sourced from e.g. imputationFunctions.R are wrappers around e.g. Beagle, and other command line programs.
#library(tidyverse); library(magrittr);
source(here::here("code","imputationFunctions.R"))
targetVCFpath<-here::here("data/Report-DCas20-5510/") # location of the targetVCF
refVCFpath<-here::here("data/")
mapPath<-here::here("data/CassavaGeneticMap/")
outPath<-here::here("output/")
outSuffix<-"DCas20_5510"
purrr::map(1:18,~runBeagle5(targetVCF=paste0(targetVCFpath,"chr",.,"_DCas20_5510.vcf.gz"),
refVCF=paste0(refVCFpath,"chr",.,"_ImputationReferencePanel_StageIIpartI_72219.vcf.gz"),
mapFile=paste0(mapPath,"chr",.,"_cassava_cM_pred.v6_91019.map"),
outName=paste0(outPath,"chr",.,"_DCas20_5510_WA_REFimputed"),
nthreads=112))Clean up Beagle log files after run. Move to sub-directory output/BeagleLogs/.
For now, the function will just do a fixed filter: AR2>0.75 (DR2>0.75 as of Beagle5.0), P_HWE>1e-20, MAF>0.005 [0.5%].
It can easily be modified in the future to include parameters to vary the filter specifications.
Input parameters
#' @inPath path to input VCF-to-be-filtered, can be left null if path included in @inName . Must end in "/"
#' @inName name of input VCF file EXCLUDING file extension. Assumes .vcf.gz
#' @outPath path where filtered VCF and related are to be stored.Can be left null if path included in @outName . Must end in "/".
#' @outName name desired for output EXCLUDING extension. Output will be .vcf.gz Loop to filter all 18 VCF files in parallel
inPath<-here::here("output/")
outPath<-here::here("output/")
source(here::here("code","imputationFunctions.R"))
require(furrr); options(mc.cores=18); plan(multiprocess)
future_map(1:18,~postImputeFilter(inPath=inPath,
inName=paste0("chr",.,"_DCas20_5510_WA_REFimputed"),
outPath=outPath,
outName=paste0("chr",.,"_DCas20_5510_WA_REFimputedAndFiltered")))Check what’s left
library(tidyverse); library(magrittr);
# Make binary plink
pathIn<-"/home/jj332_cas/marnin/NRCRI_2020GS/output/"
require(furrr); options(mc.cores=18); plan(multiprocess)
future_map(1:18,~system(paste0("export PATH=/programs/plink-1.9-x86_64-beta3.30:$PATH;",
"plink --vcf ",pathIn,"chr",.,
"_DCas20_5510_WA_REFimputedAndFiltered.vcf.gz ",
"--make-bed --const-fid ",
"--out ",pathIn,"chr",.,
"_DCas20_5510_WA_REFimputedAndFiltered")))
# Recode to dosage
future_map(1:18,~system(paste0("export PATH=/programs/plink-1.9-x86_64-beta3.30:$PATH;",
"plink --bfile ",pathIn,"chr",.,
"_DCas20_5510_WA_REFimputedAndFiltered ",
"--recode A ",
"--out ",pathIn,"chr",.,
"_DCas20_5510_WA_REFimputedAndFiltered")))
# Genome-wide dosage (for use in R)
snps<-future_map(1:18,~read.table(paste0(pathIn,"chr",.,"_DCas20_5510_WA_REFimputedAndFiltered.raw"), stringsAsFactor=F, header = T) %>%
dplyr::select(-FID,-PAT,-MAT,-SEX,-PHENOTYPE) %>%
column_to_rownames(var = "IID") %>%
as.matrix()) %>%
reduce(.,cbind)
dim(snps)
# [1] 395 61045
saveRDS(snps,file = paste0(pathIn,"DosageMatrix_DCas20_5510_WA_REFimputedAndFiltered.rds"))