# #——knitr回声= FALSE,结果=“隐藏 "---------------------------------------- 库(knitr) opts_chunk美元集(整洁= FALSE, dev =“png”,无花果。显示=“隐藏”,fig.width = 10,无花果。身高= 8,消息= FALSE) # #——style-knitr eval = TRUE,呼应= FALSE,结果= "飞机 "-------------------- BiocStyle:乳胶 () ## ---- loadpackage,回声= FALSE ----------------------------------------------- # 为了打印版本号低于图书馆(“flowMap ") ## ---- =“隐藏”选项,结果,回声= FALSE -------------------------------------- 选项(数字= 3,宽度= 80,提示= ",继续 =" ") ## ---- dataPrepExample,回声= TRUE ----------------------------------------------- sam1 < - read.table(执行(“extdata / sample.txt”、包=“flowMap”),头= T) str (sam1)表(sam1 $ id) # #——displayData -------------------------------------------------------------- sam1 < - read.table(执行(“extdata / sample.txt”、包=“flowMap”),头= T) sam2 < read.table(执行(“extdata / sample.txt”、包=“flowMap”),header=T) table(sam1$id) table(sam2$id) ## ----makeplotSelfruns1,dev='pdf'，echo=TRUE,warning=FALSE---------------------- mat1 = sam1[sam1$id==1，] mat2 = sam2[sam2$id==3，] #将两个cell population中的事件合并到# make pooled data mat = rbind(mat1,mat2) #从pooled data中采样100个事件sampleSize = 100 #在100个事件中，从两个细胞群样本事件#这样的细胞群成员的比例是相同的#池数据nn1 =圆(sampleSize *表(垫$ id) [1] / nrow(垫))nn2 =圆(sampleSize *表(垫$ id) [2] / nrow(垫))submat = rbind (mat1[样本(nrow (mat1) nn1),), mat2[样本(nrow (mat2) nn2),]) colnames (submat)[5] =“山姆”# 100事件情节MST g1 = makeFRMST (submat)标准(mar = c(0, 0, 0, 0))情节(g1 $ g, vertex.label.cex = 0.01,布局= layout.fruchterman.reingold (g1 $ g )) ## ---- makeplotSelfruns2 dev =“pdf”,呼应= TRUE,警告= FALSE ---------------------- mat1 = sam1 (sam1 $ id = = 4,);mat2 = sam2 (sam2 $ id = = 5)垫= rbind (mat1 mat2) sampleSize = 100 nn1 =圆(sampleSize *表(垫$ id) [1] / nrow(垫))nn2 =圆(sampleSize *表(垫$ id) [2] / nrow(垫))submat = rbind (mat1[样本(nrow (mat1) nn1),), mat2[样本(nrow (mat2) nn2),]) colnames (submat)[5] =“山姆”g1 = makeFRMST (submat)标准(mar = c(0, 0, 0, 0))情节(g1 $ g, vertex.label.cex = 0.01, = layout.fruchterman.reingold布局(g1 $ g )) ## ---- makeplotSelfruns3 dev =“pdf”,呼应= TRUE,警告= FALSE ---------------------- mat1 = sam1 (sam1 $ id = = 6) mat2 =sam2[sam2$id==6,] mat1$id=1; mat2$id=2 mat = rbind(mat1,mat2) sampleSize = 100 nn1 = round(sampleSize*table(mat$id)[1]/nrow(mat)) nn2 = round(sampleSize*table(mat$id)[2]/nrow(mat)) submat = rbind(mat1[sample(nrow(mat1),nn1),],mat2[sample(nrow(mat2),nn2),]) colnames(submat)[5] = "sam" g1 = makeFRMST(submat) par(mar=c(0,0,0,0)) plot(g1$g,vertex.label.cex=0.01,layout=layout.fruchterman.reingold(g1$g)) ## ----displayData2------------------------------------------------------------- sam1 <- read.table(system.file("extdata/sample.txt" ,package="flowMap"),header=T) sam2 <- read.table(system.file("extdata/sample.txt" ,package="flowMap"),header=T) table(sam1$id) table(sam2$id) ## ----compareSampleSelf,dev='pdf',warning=FALSE-------------------------------- res1 = getFRest(sam1,sam2,sampleMethod="proportional",sampleSize=100, ndraws=100,estStat="median",ncores=NULL) res1@ww library(gplots) par(mar=c(0,0,0,0)) heatmapCols <- colorRampPalette(c("red","yellow","white","blue"))(50) heatmap.2(res1@ww,trace="none",col=heatmapCols,symm=FALSE,dendrogram="none", Rowv=FALSE,Colv=FALSE,xlab="Sample 2",ylab="Sample 1") ## ----plotSelfpval,dev="pdf",echo=TRUE----------------------------------------- library(gplots) par(mar=c(0,0,0,0)) heatmapCols <- colorRampPalette(c("red","yellow","white","blue"))(50) heatmap.2(res1@pNorm,trace="none",col=heatmapCols,symm=FALSE,dendrogram="none", Rowv=FALSE,Colv=FALSE,xlab="Sample 2",ylab="Sample 1") ## ----plotSelfpvalhist,dev="pdf",echo=TRUE------------------------------------- hist(res1@pNorm,xlab="log10 p-value histogram",main="") ## ----plotMultipval,dev="pdf",echo=TRUE---------------------------------------- resMulti = makeDistmat(samples=list(sam1,sam2),sampleSize=100,ndraws=100) require(gplots) par(mar=c(0,0,0,0)) heatmapCols <- colorRampPalette(c("red","yellow","white","blue"))(50) heatmap.2(resMulti$distmat,trace="none",col=heatmapCols,symm=FALSE,dendrogram="none", Rowv=FALSE,Colv=FALSE) ## ----sessionInfo,results="asis",echo=FALSE, eval=TRUE------------------------- toLatex(sessionInfo()) ## ----resetOptions, results='hide', echo=FALSE--------------------------------- options(prompt="> ", continue="+ ") ## ----closeSockets,echo=FALSE-------------------------------------------------- closeSockets <- function() { allCon <- showConnections() socketCon <- as.integer(rownames(allCon)[allCon[, "class"] == "sockconn"]) sapply(socketCon, function(ii) close.connection(getConnection(ii)) ) } closeSockets()