heatdiagram(limma)
heatdiagram()所属R语言包：limma
Stemmed Heat Diagram
源于热图
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Creates a heat diagram showing the co-regulation of genes under one condition with a range of other conditions.
创建一个热图显示，与一系列的其他条件的情况下共同的基因调控。
用法----------Usage----------
heatDiagram(results,coef,primary=1,names=NULL,treatments=colnames(coef),limit=NULL,orientation="landscape",low="green",high="red",cex=1,mar=NULL,ncolors=123,...)
heatdiagram(stat,coef,primary=1,names=NULL,treatments=colnames(stat),critical.primary=4,critical.other=3,limit=NULL,orientation="landscape",low="green",high="red",cex=1,mar=NULL,ncolors=123,...)
参数----------Arguments----------
参数：results
TestResults matrix, containing elements -1, 0 or 1, from decideTests
TestResults矩阵，包含元素-1，0或1，从decideTests
参数：stat
numeric matrix of test statistics. Rows correspond to genes and columns to treatments or contrasts between treatments.
测试统计的数字矩阵。行对应基因治疗或治疗之间的对比和列。
参数：coef
numeric matrix of the same size as stat. Holds the coefficients to be displayed in the plot.
数字矩阵的大小相同stat。持有系数图显示。
参数：primary
number or name of the column to be compared to the others. Genes are included in the diagram according to this column of stat and are sorted according to this column of coef. If primary is a name, then stat and coef must have the same column names.
比别人号码或列名。基因图根据这个stat列和按这个coef列进行排序。 primary如果是一个名字，然后stat和coef必须有相同的列名。
参数：names
optional character vector of gene names
基因名称可选的特征向量
参数：treatments
optional character vector of treatment names
治疗名称可选的特征向量
参数：critical.primary
critical value above which the test statistics for the primary column are considered significant and included in the plot
以上主列的测试统计数据被认为是显着的和图的临界值
参数：critical.other
critical value above which the other test statistics are considered significant. Should usually be no larger than critical.primary although larger values are permitted.
临界值以上的其他检验统计量被认为是显着的。通常应比critical.primary虽然允许值越大。
参数：limit
optional value for coef above which values will be plotted in extreme color. Defaults to max(abs(coef)).
coef高于该值将在极端的颜色绘制的可选值。 max(abs(coef))默认。
参数：orientation
"portrait" for upright plot or "landscape" for plot orientated to be wider than high. "portrait" is likely to be appropriate for inclusion in printed document while "landscape" may be appropriate for a presentation on a computer screen.
"portrait"直立图或"landscape"图导向大于高宽。 "portrait"可能是适合纳入印刷文件的同时"landscape"可能为在计算机屏幕上的演示适当。
参数：low
color associated with repressed gene regulation
颜色相关的基因调控压抑
参数：high
color associated with induced gene regulation
与诱导的基因表达调控相关的颜色
参数：ncolors
number of distinct colors used for each of up and down regulation
不同颜色的数量高达每下调
参数：cex
factor to increase or decrease size of column and row text
增加或减少的列和行文字的大小的因素
参数：mar
numeric vector of length four giving the size of the margin widths. Default is cex*c(5,6,1,1) for landscape and cex*c(1,1,4,3) for portrait.
长度为4的数字矢量边距宽度的大小。默认是cex*c(5,6,1,1)景观和cex*c(1,1,4,3)肖像。
参数：...
any other arguments will be passed to the image function
任何其他参数将被传递给image函数
Details
详情----------Details----------
Users are encouraged to use heatDiagram rather than heatdiagram as the later function may be removed in future versions of limma.
我们鼓励用户使用heatDiagram而不是heatdiagram为以后的功能可能会在未来版本的limma删除。
This function plots an image of gene expression profiles in which rows (or columns for portrait orientation) correspond to treatment conditions and columns (or rows) correspond to genes. Only genes which are significantly differentially expressed in the primary condition are included. Genes are sorted by differential expression under the primary condition.
这个函数绘制的行（或列）为纵向符合治疗条件和列（或行）对应基因的基因表达谱的形象。唯一的基因有显着差异表达的首要条件。下差异表达的基因排序的首要条件。
Note: the plot produced by this function is unique to the limma package. It should not be confused with "heatmaps" often used to display results from cluster analyses.
注：此功能产生的图是唯一的limma包。从聚类分析的结果显示与经常使用的“热图”，它不应该被混淆。
值----------Value----------
An image is created on the current graphics device.
当前图形设备上创建一个图像。
作者（S）----------Author(s)----------
Gordon Smyth
参见----------See Also----------
image.
image。
举例----------Examples----------
if(require("sma")) {
data(MouseArray)
MA <- normalizeWithinArrays(mouse.data,layout=mouse.setup)
design <- cbind(c(1,1,1,0,0,0),c(0,0,0,1,1,1))
fit <- lmFit(MA,design=design)
contrasts.mouse <- cbind(Control=c(1,0),Mutant=c(0,1),Difference=c(-1,1))
fit <- eBayes(contrasts.fit(fit,contrasts=contrasts.mouse))
results <- decideTests(fit,method="global",p=0.1)
heatDiagram(results,fit$coef,primary="Difference")
}
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。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-2-25 23:15:57
