# #设置,呼应= FALSE,缓存= FALSE ------------------------------------------ ## 数量> = 10 ^ 5将用科学记数法表示,# #和圆形的2位数选项(scipen = 1位数= 4 ) ## ---- 消息= FALSE ----------------------------------------------------------- 库(DEScan2)图书馆(RUVSeq)库(“刨边机”)BiocParallel::注册(BiocParallel:: SerialParam ()) ## ---- eval = TRUE ---------------------------------------------------------------- bam。文件< - list.files(执行(file.path(“extdata”、“砰”),包=“DEScan2”),模式=“砰”美元,full.names = TRUE) # #——findPeaks缓存= TRUE, eval = FALSE ---------------------------------------- # peaksGRL < - DEScan2:: = bam findPeaks(文件。files[1]， filetype="bam"， genomeName="mm9"， # binSize=50, minWin=50, maxWin=1000, zthresh=10, minCount=0.1, sigwin=10， # minCompWinWidth=5000, maxCompWinWidth=10000, save=FALSE， # outputFolder="peaks"， force=TRUE, onlyStdChrs=TRUE, chr=NULL, verbose=FALSE ----------------------- peaks. ## ----finalRegions, cache=TRUE, eval=TRUE, message=FALSE----------------------- peaks. #文件< -系统。file(file.path("extdata"，"peaks"，"RData"，"peaksGRL_all_files.rds")， package="DEScan2") peaksGRL <- readRDS(peaks.file) regionsGR <- DEScan2::finalRegions(peakSamplesGRangesList=peaksGRL, zThreshold=10, minCarriers=3, saveFlag=FALSE, outputFolder=NULL, verbose=FALSE) head(regionsGR) ## ----countFinalRegions, cache=TRUE, eval=TRUE, message=FALSE------------------ bam。path <- system.file(file.path("extdata"，"bam")， package="DEScan2") finalRegions <- DEScan2::countFinalRegions(regionsGRanges=regionsGR, readsFilePath=bam. path)。路径,文件类型=“砰”,minCarriers = 1, genomeName =“mm9 onlyStdChrs = TRUE, saveFlag = FALSE, verbose = FALSE)计数< - SummarizedExperiment::分析(finalRegions) <——SummarizedExperiment:: rowRanges (finalRegions区域 ) ## ---- eval = TRUE --------------------------------------------------------------- 计数< -计数(地区k-carriers > = 4,美元)计数< -计数(rowSums(计数)> 0)colnames(计数)< - c(“FC1”、“FC4”、“盐酸”、“HC4”、“FC6”、“FC9”、“HC6”,“HC9”)计数< -计数(、订单(colnames(计数)))RUV,头(计数)# #——政府缓存= TRUE, eval = TRUE ----------------------------------------------- 库(RColorBrewer)颜色< -布鲁尔。pal(3， "Set2") set <- EDASeq::betweenLaneNormalization(counts, which =" upper") groups <- matrix(c(1:8)， nrow=2, byrow=TRUE) trt <- factor(c(rep("FC"， 4)， rep("HC"， 4))) ## ----rawPlot, fig.width=3.5, fig.height=3.5, fig.show='hold'------------------ EDASeq::plotRLE(set, outline=FALSE, ylim=c(-4, 4)， col=colors[trt]， main="No Normalization RLE") EDASeq:: plotca (set, col=colors[trt]， main="No Normalization PCA"， labels=FALSE, pch=19) ## ----ruvPlot, fig.width=3.5, fig.height=3.5，fig.show = '举行 '------------------ k < - 4 s < - RUVSeq: RUVs(集,cIdx = rownames(组),scIdx =组、k = k) EDASeq:: plotRLE (normalizedCounts新元,大纲= FALSE, ylim = c(4, 4),坳=颜色泰爱泰党,主要=“规范化RLE”)EDASeq:: plotPCA (normalizedCounts新元,坳=颜色泰爱泰党,主要=“归一化PCA”标签= FALSE, pch = 19) # #——测试缓存= TRUE, eval = TRUE ---------------------------------------------- < -设计模型。matrix(~0 + trt + s$W) colnames(design) <- c(levels(trt)， paste0("W"， 1:k)) y <- edgeR::DGEList(counts=counts, group=trt) y <- edgeR::estimateDisp(y, design) fit <- edgeR::glmQLFit(y, design, robust=TRUE) con <- limma::makeContrasts(FC - HC, levels=design) qlf <- edgeR::glmQLFTest(fit，对比度=con) res <- edgeR::topTags(qlf, n=Inf，)p.value = 0.05)头(res表)美元暗(res表)美元地区[rownames (res美元表 )] ## ---- eval = FALSE -------------------------------------------------------------- # 库(BiocParallel) # # peaksGRL < = bam - DEScan2:: findPeaks(文件。files[1]， filetype="bam"， genomeName="mm9"， # binSize=50, minWin=50, maxWin=1000, zthresh=10, minCount=0.1, sigwin=10， # minCompWinWidth=5000, maxCompWinWidth=10000, save=FALSE， # outputFolder="peaks"， force=TRUE, onlyStdChrs=TRUE, chr=NULL, verbose=FALSE， # BPPARAM=BiocParallel::MulticoreParam(2))