## ----- echo = false，结果=“ hide”，messages = false -------------------------------------------------------------------------------------------------------------------------require（knitr）opts_chunk $ set（error = false，message = false，parning = false）## ----设置，echo = false，message，message = false ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------库（CYDAR）库（BioCparallel）寄存器（SerialParam（））set.seed（100）## ---------------------------------------------------------------------------------------------------------------------------------------------- 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（rnorm（nda*nmarkers，nmarkers，，，，，，，nmarkers，，）down.pos，0.3），ncol = nmarkers），矩阵（rnorm（nda*nmarkers，up.pos，0.3），ncol = nmarkers））组合[，31]] <-rnorm（nrow（组合），1，0.5）＃最后一个标记是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（presition）））{sutt < - list（complined [sample.id == i）,, drop = fals]）names（quits）<-paste0（“ sample”，i）collected.exprs [[i]] seq_along(conditions)) collected.exprs <- ncdfFlowSet(as(collected.exprs, "flowSet")) ## ----------------------------------------------------------------------------- pool.ff <- poolCells(collected.exprs) ## ----------------------------------------------------------------------------- library(flowCore) trans <- estimateLogicle(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$table[is.sig,] coords <- prcomp(sig.coords) ## ----------------------------------------------------------------------------- plotSphereLogFC(coords$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 <- markernames(cd) for (i in order(all.markers)) { plotSphereIntensity(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()