Merge branch 'main' of etulab.univ-amu.fr:t19016063/m2reprod

src/download_data.R

@@ -50,5 +50,3 @@ if (actual_md5 == expected_md5) {
   stop("MD5 checksum does not match!")
 }
 
-
-

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")
@@ -9,9 +10,36 @@ if (!require("snpStats", quietly = TRUE))
 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")
+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)
+