1进入文件数据文件夹和激活conda
cd /
cd /mnt/d/peng/goat/sixregions
conda activate seletion
R
library(detectRUNS)
genotypeFilePath <- ("/mnt/d/peng/goat/sixregions/Africa.ped")
mapFilePath <- ("/mnt/d/peng/goat/sixregions/Africa.map")
2进行ROH检测(consecutiveRuns method)
consecutiveRuns <- consecutiveRUNS.run(
genotypeFile =genotypeFilePath,
mapFile = mapFilePath,
minSNP = 20,
ROHet = FALSE,
maxGap = 10^6,
minLengthBps = 200000,
maxOppRun = 1,
maxMissRun = 1
)
summaryList <- summaryRuns( runs = consecutiveRuns, mapFile = mapFilePath, genotypeFile = genotypeFilePath, Class = 4, snpInRuns = TRUE)
str (summaryList)
3输出结果
write.csv (summaryList summary_ROH_percentage_chr, file ="/mnt/d/peng/goat/sixregions/summary_ROH_percentage_chr.csv", sep =" ", row.names =TRUE, col.names =TRUE, quote =TRUE)
write.csv (summaryList summary_ROH_percentage , file ="/mnt/d/peng/goat/sixregions/summary_ROH_percentage .csv", sep =" ", row.names =TRUE, col.names =TRUE, quote =TRUE)
write.csv (summaryList summary_ROH_mean_class, file ="/mnt/d/peng/goat/sixregions/summary_ROH_mean_class.csv", sep =" ", row.names =TRUE, col.names =TRUE, quote =TRUE)
write.csv (summaryList result_Froh_chromosome_wide, file ="/mnt/d/peng/goat/sixregions/result_Froh_chromosome_wide.csv", sep =" ", row.names =TRUE, col.names =TRUE, quote =TRUE)
write.csv (summaryList SNPinRun , file ="/mnt/d/peng/goat/sixregions/SNPinRun-20.csv", sep =" ", row.names =TRUE, col.names =TRUE, quote =TRUE)