## ----getWin, message=FALSE,warning=FALSE-------------------------------------- library(strandCheckR) files <- system.file( "extdata",c("s1.sorted.bam","s2.sorted.bam"),package = "strandCheckR" ) win <- getStrandFromBamFile(files, sequences = "10") # shorten the file name win$File <- basename(as.character(win$File)) win ## ----highestCoverage, eval=TRUE, message=FALSE,warning=FALSE------------------ head(win[order((win$NbPos+win$NbNeg),decreasing=TRUE),]) ## ----paired end, eval=TRUE,message=FALSE,warning=FALSE------------------------ fileP <- system.file("extdata","paired.bam",package = "strandCheckR") winP <- getStrandFromBamFile(fileP, sequences = "10") winP$File <- basename(as.character(winP$File)) #shorten file name winP ## ----intersect, eval=TRUE, warning=FALSE,message=FALSE------------------------ library(TxDb.Hsapiens.UCSC.hg38.knownGene) annot <- transcripts(TxDb.Hsapiens.UCSC.hg38.knownGene) #add chr before the sequence names to be consistent with the annot data win$Seq <- paste0("chr",win$Seq) win <- intersectWithFeature( windows = win, annotation = annot, overlapCol = "OverlapTranscript" ) win ## ----plotHist, eval=TRUE, message=FALSE,warning=FALSE------------------------- plotHist( windows = win, groupBy = c("File","OverlapTranscript"), normalizeBy = "File", scales = "free_y" ) ## ----plotHistPaired, eval=TRUE,message=FALSE,warning=FALSE-------------------- plotHist( windows = winP, groupBy = "Type", normalizeBy = "Type", scales = "free_y" ) ## ----heatMap, eval=TRUE, message = FALSE, warning=FALSE----------------------- plotHist( windows = win, groupBy = c("File","OverlapTranscript"), normalizeBy = "File", heatmap = TRUE ) ## ----plotwin,eval=TRUE,message=FALSE,warning=FALSE---------------------------- plotWin(win, groupBy = "File") ## ----filterDNA, eval=TRUE, message=FALSE, warning=FALSE, results=FALSE-------- win2 <- filterDNA( file = files[2], sequences = "10", destination = "s2.filter.bam", threshold = 0.7, getWin = TRUE ) ## ----compare,eval=TRUE,message=FALSE,warning=FALSE---------------------------- win2$File <- basename(as.character(win2$File)) win2$File <- factor(win2$File,levels = c("s2.sorted.bam","s2.filter.bam")) library(ggplot2) plotHist(win2,groupBy = "File",normalizeBy = "File",scales = "free_y") + ggtitle("Histogram of positive proportions over all sliding windows before and after filtering reads coming from double strand DNA")