## ----设置，echo = false，结果='hide'-----------------------------------------------------------------------------库（“ knitr”）＃opts_chunk $ set（fig.align =“ center”，fig.width = 7，fig.height = 7）#options（width = 90）-lib, message=FALSE, results='hide', warning=FALSE------------------------ library(flowVS) #load library ## ---- hd，echo = true，警告= false，图。在高清数据中。Bartlett \的统计数据（Y轴）是根据不同辅因子（X轴）转换数据后从密度峰值计算的。在Bartlett \的统计数据最小的情况下，获得了最佳辅助因子（由红色圆圈表示）。---##示例1：Flowvs包装数据（HD）的健康数据（HD）##标识CD3和CD4通道辅助因子的最佳辅助因子= estparamflowvs（HD [1：5]，Channels = C（'CD3'，'CD4'））## ------------- echo，echo = true，parning = false，false，fight.cap ='数据之后的密度图通过使用最佳辅助因子的ASINS转换进行转换。“ ---- ##在所有样品中转换CD3和CD4通道HD.VS = TransFlowVS（HD，Channels = C（'CD3'，'CD4'），cofactors，cofactors）##密度图（来自flowviz软件包）密度图（〜CD3+CD4，HD.VS，main =“ HD数据中的转染CD3和CD4通道”）## ------------------ ITN，echo = true，警告，警告= false，图。='High'，Fig.Show ='Hold'，Out.Width ='。49\\ lineWidth'，图Cap ='在ITN数据中转换两个荧光通道。Bartlett \的统计数据（Y轴）是根据不同辅因子（X轴）转换数据后从密度峰值计算的。 An optimum cofactor is obtained where Bartlett\'s statistics is minimum (indicated by red circles).'---- ## Example 2: ITN data from flowStats package suppressMessages(library(flowStats)) data(ITN) # identify lymphocytes ITN.lymphs = fsApply(ITN,lymphs, list("FS"=c(200, 600),"SS"=c(0, 400)), "FSC", "SSC",FALSE) ## identify optimum cofactor for CD3 and CD4 channels cofactors = estParamFlowVS(ITN.lymphs[1:5],channels=c('CD3', 'CD4')) ## ----densityITN, echo=TRUE, warning=FALSE, fig.cap='The density plots after the data is transformed by asins transformation with the optimum cofactors.'---- ## transform CD4 channel in all samples ITN.VS = transFlowVS(ITN.lymphs, channels=c('CD3', 'CD4'), cofactors) ## density plot (from flowViz package) densityplot(~CD3+CD4, ITN.VS, main="Transfromed CD3 and CD4 channels in ITN data") ## ----microVS, echo=TRUE, warning=FALSE, fig.width=5, fig.height=5------------- suppressMessages(library(vsn)) data(kidney) kidney.microVS = microVS(exprs(kidney)) #variance stabilization ## ----vsn, echo=TRUE, warning=FALSE, fig.width=4.5, fig.height=4, fig.show='hold', fig.align='center', fig.cap='Variance stabilization of the Kidney microarray data by flowVs and vsn packages.'---- suppressMessages(library(vsn)) data(kidney) kidney.vsn = vsn2(exprs(kidney)) #variance stabilization by vsn plotMeanSd(kidney.microVS, main="Kidney data: VS by flowVS") plotMeanSd(exprs(kidney.vsn), main="Kidney data: VS by vsn") ## ----sessionInfo, results = 'asis', eval = TRUE, echo = TRUE------------------ toLatex(sessionInfo())