heatplot(made4)
heatplot()所属R语言包：made4
Draws heatmap with dendrograms.
绘制与聚类的热图。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
heatplot calls heatmap.2 using a red-green colour scheme by default. It also draws dendrograms of the cases and variables using correlation similarity metric and average linkage clustering as described by Eisen. heatplot is useful for a
heatplotheatmap.2使用默认情况下，一红一绿的配色方案。它还提请使用相关相似性度量和平均连锁聚类艾森形容情况和变量聚类。 heatplot是一个有用的
用法----------Usage----------
参数----------Arguments----------
参数：dataset
a matrix, data.frame, ExpressionSet or marrayRaw-class. If the input is gene expression data in a matrix or data.frame. The rows and columns are expected to contain the variables (genes) and cases (array samples) respectively.
matrix，data.frame，ExpressionSet或marrayRaw-class。如果输入的是一个matrix或data.frame的基因表达数据。预计包含的变量（基因）和例（阵列样品）分别行和列。
参数：dend
A character indicating whether dendrograms should be drawn for both rows and columms "both", just rows "row" or column "column" or no dendrogram "none". Default is both.
字符指示是否应为两行和columms“既”，只是行“行”或列“列”或没有树状“无”绘制聚类。默认是两个。
参数：cols.default
Logical. Default is TRUE. Use blue-brown color scheme.
逻辑。默认TRUE。使用蓝色褐色计划。
参数：lowcol, highcol
Character indicating colours to be used for down and upregulated genes when drawing heatmap if the default colors are not used, that is cols.default = FALSE.
字符显示颜色下来，上调基因绘制热图时，如果不使用默认的颜色，是cols.default = FALSE。
参数：scale
Default is row. Scale and center either "none","row", or "column").
默认是行。规模和中心，无论是“无”，“行”，或“列”）。
参数：classvec,classvec2
A factor or vector which describes the classes in columns or rows of the dataset. Default is NULL. If included, a color bar including the class of each column (array sample) or row (gene) will be drawn. It will automatically add to either the columns or row, depending if the length(as.character(classvec)) ==nrow(dataset) or ncol(dataset).
一个factor或vector这说明在列或行dataset类。默认NULL。如果包括，彩条，包括每列类（阵列样品）或行（基因）将绘制。它会自动添加到列或行，根据长度（as.character（classvec））==“NROW（集）或NCOL”（集）。
参数：classvecCol
A vector of length the number of levels in the factor classvec. These are the colors to be used for the row or column colorbar. Colors should be in the same order, as the levels(factor(classvec))
长度为向量的数量因素classvec的水平。这些是将要使用的行或列的彩条的颜色。颜色应该是在同一顺序的水平，（因子（classvec））
参数：distfun
A character, indicating function used to compute the distance between both rows and columns. Defaults to 1- Pearson Correlation coefficient
一个字符，表示用来计算行和列之间的距离的功能。默认为1 - 皮尔森相关系数
参数：method
The agglomeration method to be used. This should be one of '"ward"', '"single"','"complete"', '"average"', '"mcquitty"', '"median"' or '"centroid"'. See hclust for more details. Default is "ave"
结块的方法来使用。这应该是一个“病房”，“单”“，”完成“，”平均“，”mcquitty“，”中位数“或”“重心“。看到hclust更多细节。默认是“大道”
参数：dualScale
A logical indicating whether to scale the data by row and columns. Default is TRUE
一个logical指示是否scale由行和列的数据。默认值是TRUE
参数：zlim
A vector of length 2, with lower and upper limits using for scaling data. Default is c(-3,3)
一个vector长度为2，上下缩放数据的使用限制。默认是C（-3,3）
参数：scaleKey
A logical indicating whether to draw a heatmap color-key bar. Default is TRUE
一个logical指示是否绘制热图色键栏。默认值是TRUE
参数：returnSampleTree
A logical indicating whether to return the sample (column) tree. If TRUE it will return an object of class dendrogram. Default is FALSE </table>
一个logical表示是否返回的样本（列）树。如果是TRUE，它会返回一个对象类dendrogram。默认值为FALSE </ TABLE>
参数：...
further arguments passed to or from other methods.
通过进一步的论据或其他方法。
Details
详情----------Details----------
The hierarchical plot is produced using average linkage cluster analysis with a correlation metric distance. heatplot calls heatmap.2 in the R package gplots.
使用相关的度量距离平均连锁聚类分析层次的图。 heatplot要求heatmap.2R包gplots的。
NOTE: We have changed heatplot scaling in made4 (v 1.19.1) in Bioconductor v2.5. Heatplot by default dual scales the data to limits of -3,3. To reproduce older version of heatplot, use the parameters dualScale=FALSE, scale="row".
注：我们已经改变了Bioconductor V2.5 made4 heatplot缩放（V 1.19.1）。 heatplot由默认的数据限制-3,3双尺度。为了重现老年人版本heatplot，使用的参数dualScale = FALSE，规模=“行”。
值----------Value----------
Plots a heatmap with dendrogram of hierarchical cluster analysis. If returnSampleTree is TRUE, it returns an object dendrogram which can be manipulated using
聚类分析聚类分析的热图绘制。如果returnSampleTree为TRUE，它返回一个dendrogram这可以被操纵的对象，使用
注意----------Note----------
Because Eisen et al., 1998 use green-red colours for the heatmap heatplot uses these by default however a blue-red or yellow-blue are easily obtained by
但由于艾森等人，1998年使用绿红颜色的热图heatplot默认情况下使用这些蓝色红色或黄色，蓝色很容易获得
作者（S）----------Author(s)----------
Aedin Culhane
参考文献----------References----------
Genome-Wide Expression Patterns. Proc Natl Acad Sci USA 95, 14863-8.
参见----------See Also----------
See also as hclust,
看到hclust，
举例----------Examples----------
data(khan)
## Change color scheme[＃更改配色方案]
heatplot(khan$train[1:30,])
heatplot(khan$train[1:30,], cols.default=FALSE, lowcol="white", highcol="red")
## Add labels to rows, columns[＃添加标签行，列]
heatplot(khan$train[1:26,], labCol = c(64:1), labRow=LETTERS[1:26])
## Add a color bar[＃添加一个彩条]
heatplot(khan$train[1:26,], classvec=khan$train.classes)
heatplot(khan$train[1:26,], classvec=khan$train.classes, classvecCol=c("magenta", "yellow", "cyan", "orange"))
## Change the scaling to the older made4 version (pre Bioconductor 2.5)[＃将扩展到旧made4版本（前Bioconductor 2.5）]
heatplot(khan$train[1:26,], classvec=khan$train.classes, dualScale=FALSE, scale="row")
## Getting the members of a cluster and manuipulating the tree[＃获取聚类成员和manuipulating树，]
sTree<-heatplot(khan$train, classvec=khan$train.classes, returnSampleTree=TRUE)
class(sTree)
plot(sTree)
## Cut the tree at the height=1.0[＃切树的高度= 1.0]
lapply(cut(sTree,h=1)$lower, labels)
## Zoom in on the first cluster[＃放大的第一个簇]
plot(cut(sTree,1)$lower[[1]])
str(cut(sTree,1.0)$lower[[1]])
## Visualizing results from an ordination using heatplot[＃从使用heatplot协调可视化的结果]
if (require(ade4, quiet = TRUE)) {
res<-ord(khan$train, ord.nf=5) # save 5 components from correspondence analysis[保存5个组成部分，从对应分析]
khan.coa = res$ord
}
# Provides a view of the components of the Correspondence analysis (gene projection) [对应分析的组件提供了一个视图（基因预测）]
heatplot(khan.coa$li, dend="row", dualScale=FALSE) # first 5 components, do not cluster columns, only rows.[前5个元件，不聚类列，仅行。]
# Provides a view of the components of the Correspondence analysis (sample projection) [对应分析的组件提供了一个视图（样本投影）]
# The difference between tissues and cell line samples are defined in the first axis.[组织和单元样本之间的差异是指在第一轴。]
heatplot(khan.coa$co, margins=c(4,20), dend="row") # Change the margin size. The default is c(5,5)[更改边距大小。默认为C（5,5）]
# Add a colorbar, change the heatmap color scheme and no scaling of data[添加一个彩条，改变热图的配色方案并没有数据缩放]
heatplot(khan.coa$co,classvec2=khan$train.classes, cols.default=FALSE, lowcol="blue", dend="row", dualScale=FALSE)
apply(khan.coa$co,2, range)
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 2012-2-26 00:01:24
