plotSmear(edgeR)
plotSmear()所属R语言包：edgeR
Plots log-Fold Change versus log-Concentration (or, M versus A) for Count Data
图log倍对数浓度（或M对计数数据）
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Both of these functions plot the log-fold change (i.e. the log of the ratio of expression levels for each tag between two experimential groups) against the log-concentration (i.e. the overall average expression level for each tag across the two groups). To represent counts that were low (e.g. zero in 1 library and non-zero in the other) in one of the two conditions, a 'smear' of points at low A value is presented in plotSmear.
无论这些功能积数倍的变化（即每个标签两experimential组的表达水平比log）对数浓度（即整体平均为每个标记在两个组的表达水平）。代表中的两个条件之一，“涂抹”在低一个价值点计数低（如1库和其他非零零）plotSmear。
用法----------Usage----------
plotSmear(object, pair = NULL, de.tags=NULL, xlab = "logConc", ylab =
"logFC", pch = 19, cex = 0.2, smearWidth = 0.5, panel.first=grid(),
smooth.scatter=FALSE, lowess=FALSE, ...)
参数----------Arguments----------
参数：object
DGEList or DGELRT object containing data to produce an MA-plot.
DGEList或DGELRT对象包含的数据产生一个马的图。
参数：pair
pair of experimental conditions to plot (if NULL, the first two conditions are used)
对实验条件的图（NULL如果，前两个条件）
参数：de.tags
rownames for tags identified as being differentially expressed; use exactTest to identify DE genes
rownames确定为差异表达的标签，使用exactTest识别DE基因
参数：xlab
x-label of plot
X-标签的图
参数：ylab
y-label of plot
Y-图的标签
参数：pch
scalar or vector giving the character(s) to be used in the plot; default value of 19 gives a round point.
标量或矢量提供的字符（S）在图中使用默认值19给出了一个圆形的点。
参数：cex
character expansion factor, numerical value giving the amount by which plotting text and symbols should be magnified relative to the default; default cex=0.2 to make the plotted points smaller
默认字符膨胀系数，数值给图文字和符号相对应放大默认的金额;cex=0.2让小散点
参数：smearWidth
width of the smear
涂抹的宽度
参数：panel.first
an expression to be evaluated after the plot axes are set up but before any plotting takes place; the default grid() draws a background grid to aid interpretation of the plot
表达式进行评估后积轴成立，但在此之前的任何图发生;默认grid()绘制一个背景网格的图，以帮助解释
参数：smooth.scatter
logical, whether to produce a 'smooth scatter' plot using the KernSmooth::smoothScatter function or just a regular scatter plot; default is FALSE, i.e. produce a regular scatter plot
逻辑，是否产生“顺利散射”图使用的KernSmooth :: smoothScatter功能或只是一个普通的散点图;默认为FALSE，即产生一个普通的散点图
参数：lowess
logical, indicating whether or not to add a lowess curve to the MA-plot to give an indication of any trend in teh log-fold change with log-concentration
逻辑，说明是否添加一个的LOWESS曲线的主图倍德log与log浓度的变化在给任何趋势的迹象
参数：...
further arguments passed on to plot
通过进一步的论据plot
Details
详情----------Details----------
plotSmear is a more sophisticated and superior way to produce an 'MA plot'. plotSmear resolves the problem of plotting tags that have a total count of zero for one of the groups by adding the 'smear' of points at low A value. The points to be smeared are identified as being equal to the minimum estimated concentration in one of the two groups. The smear is created by using random uniform numbers of width smearWidth to the left of the minimum A. plotSmear also allows easy highlighting of differentially expressed (DE) tags.
plotSmear是一个更复杂的和卓越的方式产生一个“主图”。 plotSmear解决了绘制有加入“抹黑”点A值低的群体之一的零总数的标签问题。涂点被确定为等于估计在两组的最低浓度。涂抹创建通过使用统一编号的宽度smearWidth随机最低答：左边plotSmear还允许容易突出差异表达（DE）的标签。
值----------Value----------
A plot to the current device
到当前设备的一个图
作者（S）----------Author(s)----------
Mark Robinson, Davis McCarthy
参见----------See Also----------
maPlot
maPlot
举例----------Examples----------
y <- matrix(rnbinom(10000,mu=5,size=2),ncol=4)
d <- DGEList(counts=y, group=rep(1:2,each=2), lib.size=colSums(y))
rownames(d$counts) <- paste("tag",1:nrow(d$counts),sep=".")
d <- estimateCommonDisp(d)
plotSmear(d)
# find differential expression[寻找差异表达]
de <- exactTest(d)
# highlighting the top 500 most DE tags[突出500强最详细的标签]
de.tags <- rownames(topTags(de, n=500)$table)
plotSmear(d, de.tags=de.tags)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
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发表于 2012-2-25 17:09:35
