mod

src/tp1.R

-wdir="."
-dir.create(wdir, showWarnings = F, recursive = T)
-setwd(wdir)
-
-#library(devtools)
-#library(plyr)
-
-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)
+options(repos = c(CRAN = "https://cloud.r-project.org"))
+output_dir = "results/tp1"
+dir.create(output_dir, showWarnings = F, recursive = T)
 
 # 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)
+
+
+

workflows/Makefile

-# Makefile pour enchaîner deux scripts
-
-# Cible par défaut (si 'make' est appelé sans argument)
-all: tp1_output.txt
-
-# Première étape : exécuter download_data.R
-download_data_output.txt: ~/tp1ara/src/download_data.R
-	@echo "Running download_data.R..."
-	@Rscript ~/tp1ara/src/download_data.R > download_data_output.txt
-	@echo "download_data.R completed and output stored in download_data_output.txt."
-
-# Deuxième étape : exécuter tp1.R en utilisant le résultat du premier script
-tp1_output.txt: download_data_output.txt ~/tp1ara/src/tp1.R
-	@echo "Running tp1.R..."
-	@Rscript ~/tp1ara/src/tp1.R > tp1_output.txt
-	@echo "tp1.R completed and output stored in tp1_output.txt."
-
-# Nettoyer les fichiers générés
-clean:
-	@rm -f download_data_output.txt tp1_output.txt
-	@echo "Cleaned up output files."

workflows/makefile.v2 → workflows/makefile

@@ -18,3 +18,4 @@ results/data/penncath.bed results/data/penncath.bim results/data/penncath.fam:
 clean:
 	rm -rf results/data/penncath.bed results/data/penncath.bim results/data/penncath.fam results/data/penncath.csv results/penncath.tar.gz results/data
 
+