cd /mnt/d/peng/henan/ROH

conda activate seletion
R
library(detectRUNS)

进行ROH检测

genotypeFilePath <- ("/mnt/d/peng/henan/ROH/henan2.ped")
mapFilePath <- ("/mnt/d/peng/henan/ROH/henan2.map")
slidingRuns <- slidingRUNS.run(
genotypeFile = genotypeFilePath,
mapFile = mapFilePath,
windowSize = 50, threshold = 0.05,
minSNP = 20, ROHet = FALSE,
maxOppWindow = 1,
maxMissWindow = 1,
maxGap = 10^6,
minLengthBps = 200000,
minDensity = 1/10^5)

4. 生成统计列表

summaryList <- summaryRuns( runs = slidingRuns, mapFile = mapFilePath, genotypeFile = genotypeFilePath, Class = 2, snpInRuns = TRUE)
str (summaryList)

5输出结果

write.csv (summaryList summary_ROH_percentage_chr, file ="/mnt/d/peng/henan/ROH/summary_ROH_percentage_chr.csv", sep =" ", row.names =TRUE, col.names =TRUE, quote =TRUE)
write.csv (summaryList summary_ROH_percentage , file ="/mnt/d/peng/henan/ROH/summary_ROH_percentage .csv", sep =" ", row.names =TRUE, col.names =TRUE, quote =TRUE)
write.csv (summaryList summary_ROH_mean_class, file ="/mnt/d/peng/henan/ROH/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/henan/ROH/result_Froh_chromosome_wide.csv", sep =" ", row.names =TRUE, col.names =TRUE, quote =TRUE)
write.csv (summaryList SNPinRun , file ="/mnt/d/peng/henan/ROH/SNPinRun-all.csv", sep =" ", row.names =TRUE, col.names =TRUE, quote =TRUE)