commit tp1.R

src/tp1.R

+options(repos = c(CRAN = "https://cloud.r-project.org"))
+output_dir = "results/tp1"
+dir.create(output_dir, showWarnings = F, recursive = T)
+
+# if (!require("BiocManager", quietly = TRUE))
+#  install.packages("BiocManager")
+
+#if (!require("snpStats", quietly = TRUE))
+#  BiocManager::install("snpStats")
+
+#if (!require("SNPRelate", quietly = TRUE))
+#BiocManager::install("SNPRelate")
+
+# Charger les bibliothèques
+#library(snpStats)
+#library(SNPRelate)
+#library(devtools)
+#library(plyr)
+
+# Les données analysées nécessitant beaucoup de RAM, nous allons sélectionner aléatoirement 250000 SNPs et réecrire des fichiers bed, bim, fam
+penncath_bed_path = "results/data/penncath.bed"
+penncath_bim_path = "results/data/penncath.bim"
+penncath_fam_path = "results/data/penncath.fam"
+
+geno <- snpStats::read.plink(penncath_bed_path, penncath_bim_path, penncath_fam_path, select.snps=sample(1:861473, 25000, replace = FALSE ), na.strings = ("-9"))
+
+plink_base=file.path(output_dir, "plink_base")
+snpStats::write.plink(plink_base, snps=geno$genotypes, pedigree=geno$fam[,1], id=geno$fam[,1], mother=geno$fam[,4], sex=geno$fam[,5], phenotype=geno$fam[,6], chromosome = geno$map[,1], genetic.distance = geno$map[,3], position = geno$map[,4], allele.1 = geno$map[,5], allele.2 = geno$map[,6], na.code = ("-9"))
+
+genoBim<-geno$map
+colnames(genoBim)<-c("chr", "SNP", "gen.dist", "position", "A1", "A2")
+#head(genoBim)
+
+genotype<-geno$genotype
+#print(genotype)
+
+genoFam<-geno$fam
+#head(genoFam)
+
+# On commence par libérer de l'espace
+rm(geno)
+
+rdata_path = file.path(output_dir, "TP1_asbvg.RData")
+save.image(rdata_path)
+