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# Load lipid datasets & match SNP-Lipidomics samples | |
lipidsMalay <- read.delim("public/Lipidomic/117Malay_282lipids.txt", row.names = 1) | |
lipidsIndian <- read.delim("public/Lipidomic/120Indian_282lipids.txt", row.names = 1) | |
lipidsChinese <- read.delim("public/Lipidomic/122Chinese_282lipids.txt", row.names = 1) | |
all(Reduce(intersect, list(colnames(lipidsMalay), | |
colnames(lipidsIndian), | |
colnames(lipidsChinese))) == colnames(lipidsMalay)) # TRUE | |
lip <- rbind(lipidsMalay, lipidsIndian, lipidsChinese) | |
# Country | |
country <- sapply(list(SNP_M, SNP_I, SNP_C), function(k){ | |
nrow(k$genotypes) | |
}) | |
origin <- data.frame(sample.id = rownames(SNP$genotypes), | |
Country = factor(rep(c("M", "I", "C"), country))) | |
matchingSamples <- intersect(rownames(lip), rownames(SNP$genotypes)) | |
SNP$genotypes <- SNP$genotypes[matchingSamples,] | |
lip <- lip[matchingSamples,] | |
origin <- origin[match(matchingSamples, origin$sample.id),] | |
# Combine SNP and Lipidomics | |
genData <- list(SNP = SNP$genotype, MAP = SNP$map, LIP = lip) | |
# Write processed omics and GDS | |
save(genData, origin, file = "PhenoGenoMap.RData") | |
write.plink("convertGDS", snps = SNP$genotypes) | |
# Clear memory | |
rm(list = ls()) |
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