List of uncorrected column headers often found in GWAS Summary Statistics column headers. Note the effect allele will always be the A2 allele, this is the approach done for VCF( This is enforced with the column header corrections here and also the check allele flipping test.



dataframe with 2 columns


The code to prepare the .Rda file file from the marker file is: # Most the data in the below table comes from the LDSC github wiki data("sumstatsColHeaders") # Make additions to sumstatsColHeaders using github version of MungeSumstats- # shown is an example of adding columns for Standard Error (SE) #se_cols <- data.frame("Uncorrected"=c("SE","se","STANDARD.ERROR", # "STANDARD_ERROR","STANDARD-ERROR"), # "Corrected"=rep("SE",5)) #sumstatsColHeaders <- rbind(sumstatsColHeaders,se_cols) #Once additions are made, order & save the new mapping dataset #now sort ordering -important for logic that # uncorrected=corrected comes first sumstatsColHeaders$ordering <- sumstatsColHeaders$Uncorrected==sumstatsColHeaders$Corrected sumstatsColHeaders <- sumstatsColHeaders[order(sumstatsColHeaders$Corrected, sumstatsColHeaders$ordering,decreasing = TRUE),] rownames(sumstatsColHeaders)<-1:nrow(sumstatsColHeaders) sumstatsColHeaders$ordering <- NULL #manually move FRWQUENCY to above MAR - github issue 95 frequency <- sumstatsColHeaders[sumstatsColHeaders$Uncorrected=="FREQUENCY",] maf <- sumstatsColHeaders[sumstatsColHeaders$Uncorrected=="MAF",] if(as.integer(rownames(frequency))>as.integer(rownames(maf))){ sumstatsColHeaders[as.integer(rownames(frequency)),] <- maf sumstatsColHeaders[as.integer(rownames(maf)),] <- frequency } usethis::use_data(sumstatsColHeaders,overwrite = TRUE, internal=TRUE) save(sumstatsColHeaders, file="data/sumstatsColHeaders.rda") # You will need to restart your r session for effects to take account