# #——回声= FALSE,结果=“隐藏”,消息= FALSE ------------------------------- 需要(knitr)美元opts_chunk组(错误= FALSE,消息= FALSE,警告= FALSE) # #——风格,呼应= FALSE,结果= '飞机 '---------------------------------------- BiocStyle:减价 () ## ---- fig.cap =“图1”。宽度= ' 100 %'---------------------------------- knitr: include_graphics(“qsmooth_algo.jpg ") ## ---- load-lib、消息= FALSE -------------------------------------------------- 库(qsmooth) # #——data-1消息= FALSE,警告= FALSE ------------------------------------- 库(SummarizedExperiment)库(bodymapRat) bm_dat <——bodymapRat() #选择大脑和肝脏样本,舞台21周,只有生物代表keepColumns = (colData (bm_dat)美元器官% % c(“大脑”,"Liver")) & (colData(bm_dat)$stage == 21) & (colData(bm_dat)$techRep == 1) keepRows = rowMeans(assay(bm_dat)) > 10 #过滤低计数bm_dat_e1 <- bm_dat[keepRows,keepColumns] bm_dat_e1 ## ---- compute -qsmooth1，图.height=10，图.width=10-------------------------- library(quantro) par(mfrow=c(2,2)) pd1 <- colData(bm_dat_e1) counts1 <- assay(bm_dat_e1)[!grepl("^ERCC"， rownames(assay(bm_dat_e1)))，] pd1$group <- paste(pd1$organ, pd1$sex, sep="_") matboxplot(log2(counts1+1)， groupFactor = factor(pd1$organ)， main ="原始数据"，xaxt="n"， ylab= "表达式(log2 scale)") axis(1, at=seq_len(length(as.character(pd1$organ)))， labels=FALSE) text(seq_len(length(pd1$organ))， par("usr")[3] -2, labels= pd1$organ, srt = 90, pos = 1, xpd = TRUE) matdensity(log2(counts1+1)， groupFactor = pd1$organ, main ="原始数据"，ylab= "density"，xlab =" Expression (log1 $organ) ") legend('topright'， levels(factor(factor(pd1$organ))， col = 1:2, lty = 1) qs_norm_e1 <- qsmooth(object = counts1, group_factor = pd1$organ) +1)， qs_norm_e1 matboxplot(log2(qsmoothData(qs_norm_e1)+1)， groupFactor = pd1$organ, xaxt="n"， main =" qsmooth normalized data"， ylab =" Expression (log2 scale)") axis(1, at=seq_len(length(pd1$organ))， labels=FALSE) text(seq_len(length(pd1$organ))， par("usr")[3] -2, labels= pd1$organ, srt = 90, pos = 1，xpd = TRUE) matdensity (log2 (qsmoothData (qs_norm_e1) + 1), groupFactor = pd1 $器官,主要=“qsmooth规范化数据”,xlab =表达式(log2规模),ylab =“密度”)传说(topright,水平(因子(pd1器官美元))= 1:2,上校lty = 1) # #——plot-qsmooth1-weights ---------------------------------------------------- qsmoothPlotWeights (qs_norm_e1 ) ## ----------------------------------------------------------------------------- 票面价值(mfrow = c (2, 2)) pd1 < - colData (bm_dat_e1) counts1 < -试验(bm_dat_e1) [!grepl("^ERCC"， rownames(assay(bm_dat_e1)))，] pd1$group <- paste(pd1$organ, pd1$sex, sep="_") matboxplot(log2(counts1+1)， groupFactor = factor(pd1$organ)， main ="原始数据"，xaxt="n"， ylab= "表达式(log2 scale)") axis(1, at=seq_len(length(as.character(pd1$organ)))， labels=FALSE) text(seq_len(length(pd1$organ))， par("usr")[3] -2, labels= pd1$organ, srt = 90, pos = 1, xpd = TRUE) matdensity(log2(counts1+1)， groupFactor = pd1$organ, main ="原始数据"，ylab= "density"，xlab = "Expression (log2 scale)") legend('topright'， levels(factor(pd1$organ))， col = 1:2, lty = 1) #检索GC-content使用EDASeq:# gc <- EDASeq::getGeneLengthAndGCContent(id = rownames(bm_dat_e1)， # org =" rno") data(gc, package="qsmooth") gcContent <- gc[rownames(counts1)，2] keep <- names(gcContent)[!is.na(gcContent)] qs_norm_gc <- qsmoothGC(object = counts1[keep，]， gc=gcContent[keep]， group_factor = pd1$organ) qs_norm_gc matboxplot(log2(qsmoothData(qs_norm_gc)+1)， groupFactor = pd1$organ, xaxt="n"， main =" qsmoothGC normalized data"， ylab =" Expression (log2 scale)") axis(1, at=seq_len(length(pd1$organ))，标签= FALSE)文本(seq_len(长度(pd1器官美元)),票面价值(usr)[3] 2,标签= pd1器官美元,srt = 90, pos = 1, xpd = TRUE) matdensity (log2 (qsmoothData (qs_norm_gc) + 1), groupFactor = pd1 $器官,主要=“qsmoothGC规范化数据”,xlab =表达式(log2规模),ylab =“密度”)传说(topright,水平(因子(pd1器官美元))= 1:2,上校lty = 1) # #——session-info ------------------------------------------------------------- sessionInfo ()