## ---- echo=FALSE, results="hide", message=FALSE-------------------------- require(knitr) opts_chunk$ set（error = false，message = false，警告= false）## ----样式，echo = false，结果='asis'------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------设置，echo = false，message = false ----------------------------------------------------------------------库（Cydar）寄存器（SerialParam（））set.seed（100）## ------------------------------------------------------------------------------------------------------------------------------ ncells <-20000 nda <-200 nmarkers <-31 down.pos <-1.8 up.pos <-1.2条件<-Rep（c（“ a”，“”，“”b“），每个= 3）组合<-rbind（矩阵（rnorm（ncells*nmarkers，1.5，0.6），ncol = nmarkers），矩阵（rnorm（nda*nmarkers，down.pos，0.3），ncol = ncol = ncol = nmarkers），，矩阵（rnorm（nda*nmarkers，up.pos，0.3），ncol = nmarkers））组合[，31] <-rnorm（nrow（组合），1，0.5）＃最后标记是QC标记。组合<-10^组合＃原始强度值sample.ID <-c（示例（长度（条件），ncells，replace = true），sample（（条件==“ a”），nda，替换= true），示例（条件==“ b”），nda，替换= true））colnames（组合）< - paste0（“ marker”，seq_len（nmarkers））## -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------库（ncdfflow）Collected.exprs <-list（）for（i在seq_along（条件）））{sutt]）名称（quits）< - paste0（“ sample”，i）collected.exprs [[i]] <-poolcells（quft）} names（collected.exprs）<-paste0（“ sample”，seq_along（条件））collected.exprs <-ncdfflowset（as（Collected.exprs，“ flowset”））## -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- pool.ff <- poolCells(collected.exprs）## ----------------------------------------------------------------------------------------------------------库（FlowCore）trans <-估算元素（pool.ff，colnames（pool.ff））proc.ff <- transform(pool.ff, trans) ## ------------------------------------------------------------------------ gate.31 <- outlierGate(proc.ff, "Marker31", type="upper") gate.31 filter.31 <- filter(proc.ff, gate.31) summary(filter.31@subSet) ## ------------------------------------------------------------------------ processed.exprs <- transform(collected.exprs, trans) ## ------------------------------------------------------------------------ processed.exprs <- Subset(processed.exprs, gate.31) ## ------------------------------------------------------------------------ processed.exprs <- processed.exprs[,1:30] ## ------------------------------------------------------------------------ cd <- prepareCellData(processed.exprs) ## ------------------------------------------------------------------------ cd <- countCells(cd, tol=0.5) ## ------------------------------------------------------------------------ head(assay(cd)) ## ------------------------------------------------------------------------ head(intensities(cd)) ## ------------------------------------------------------------------------ library(edgeR) y <- DGEList(assay(cd), lib.size=cd$totals) ## ------------------------------------------------------------------------ keep <- aveLogCPM(y) >= aveLogCPM(5, mean(cd$totals)) cd <- cd[keep,] y <- y[keep,] ## ------------------------------------------------------------------------ design <- model.matrix(~factor(conditions)) y <- estimateDisp(y, design) fit <- glmQLFit(y, design, robust=TRUE) res <- glmQLFTest(fit, coef=2) ## ------------------------------------------------------------------------ qvals <- spatialFDR(intensities(cd), res$table$PValue) ## ------------------------------------------------------------------------ is.sig <- qvals <= 0.05 summary(is.sig) ## ------------------------------------------------------------------------ sig.coords <- intensities(cd)[is.sig,] sig.res <- res$table[is.sig,] coords <- prcomp(sig.coords) ## ------------------------------------------------------------------------ plotCellLogFC(coords$x[,1], coords$x[,2], sig.res$logFC) ## ----fig.width=10,fig.height=12------------------------------------------ par(mfrow=c(6,5), mar=c(2.1, 1.1, 3.1, 1.1)) limits <- intensityRanges(cd, p=0.05) all.markers <- rownames(markerData(cd)) for (i in order(all.markers)) { plotCellIntensity(coords$x[,1], coords$x[,2], sig.coords[,i], irange=limits[,i], main=all.markers[i]) } ## ------------------------------------------------------------------------ nonred <- findFirstSphere(intensities(cd), res$table$PValue) summary(nonred) ## ------------------------------------------------------------------------ all.coords <- prcomp(intensities(cd)) app <- interpretSpheres(cd, select=nonred, metrics=res$table, run=FALSE, red.coords=all.coords$x[,1:2], red.highlight=is.sig) # Set run=TRUE if you want the app to run automatically. ## ------------------------------------------------------------------------ sessionInfo()