bga(made4)
bga()所属R语言包：made4
Between group analysis
组间分析
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Discrimination of samples using between group analysis as described by
组间分析样品描述的歧视
用法----------Usage----------
bga(dataset, classvec, type = "coa", ...)
## S3 method for class 'bga'
plot(x, axis1=1, axis2=2, arraycol=NULL, genecol="gray25", nlab=10,
genelabels= NULL, ...)
参数----------Arguments----------
参数：dataset
Training 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.
训练集。一个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：classvec
A factor or vector which describes the classes in the training dataset.
一个factor或vector它描述了在训练集的类。
参数：type
Character, "coa", "pca" or "nsc" indicating which data transformation is required. The default value is type="coa".
性格，“农委会”，“PCA”或“国科会”，表明这是必需的数据转换。默认值是类型=“农委会”。
参数：x
An object of class bga. The output from bga or bga.suppl. It contains the projection coordinates from bga, the \$ls, \$co or \$li coordinates to be plotted.
对象类bga。从bga或bga.suppl输出。它包含了bga，\ $ LS，CO或\ $ \ $李坐标绘制的投影坐标。
参数：arraycol, genecol
Character, colour of points on plot. If arraycol is NULL, arraycol will obtain a set of contrasting colours using getcol, for each classes of cases (microarray samples) on the array (case) plot. genecol is the colour of the points for each variable (genes) on gene plot.
字符，颜色积点。如果arraycol是NULL，arraycol将获得一组对比鲜明的色彩，使用的情况下，每个班（芯片样品）阵列（件）图getcol，。 genecol是每个变量（基因）的基因图的点的颜色。
参数：nlab
Numeric. An integer indicating the number of variables (genes) at the end of axes to be labelled, on the gene plot.
数字。被贴上一个整数，表示在轴的变量数（基因），基因图。
参数：axis1
Integer, the column number for the x-axis. The default is 1.
整数，列数为x轴。默认值是1。
参数：axis2
Integer, the column number for the y-axis, The default is 2.
整数，y轴的列数，默认是2。
参数：genelabels
A vector of variables labels, if genelabels=NULL the row.names of input matrix dataset will be used.
一个变量标签的向量，如果genelabels=NULL输入矩阵dataset row.names将使用。
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----------
bga performs a between group analysis on the input dataset. This function calls between. The input format of the dataset is verified using array2ade4.
bga执行组之间的输入数据集的分析1。此函数调用between。该数据集的输入格式验证使用array2ade4。
Between group analysis is a supervised method for sample discrimination and class prediction. BGA is carried out by ordinating groups (sets of grouped microarray samples), that is, groups of samples are projected into a reduced dimensional space. This is most easily done using PCA or COA, of the group means. The choice of PCA, COA is defined by the parameter type.
组间分析一个样品的歧视和阶级预测的监督方法。 BGA是进行了协调组（分组芯片样品套），样品，组成一个三维空间减少预计。这是最容易使用PCA或农委会，本集团的手段。 PCA，农委会选择定义参数type。
The user must define microarray sample groupings in advance. These groupings are defined using the input classvec, which is a factor or vector.
用户必须预先定义的芯片样品分组。这些分组来定义输入classvec，这是一个factor或vector。
Cross-validation and testing of bga results:
交叉验证和测试BGA结果：
bga results should be validated using one leave out jack-knife cross-validation using bga.jackknife and by projecting a blind test datasets onto the bga axes using suppl. bga and suppl are combined in bga.suppl which requires input of both a training and test dataset. It is important to ensure that the selection of cases for a training and test set are not biased, and generally many cross-validations should be performed. The function randomiser can be used to randomise the selection of training and test samples.
BGA验证结果应使用离开了杰克刀交叉验证使用bga.jackknife和BGA轴投射到盲目的测试数据集，使用suppl，。 bga和supplbga.suppl需要的训练和测试数据集的输入相结合。这一点很重要，以确保培训和测试集的情况下选择不偏颇，并应进行一般许多交叉的验证。的功能randomiser可以用来随机选择的训练和测试样本。
Plotting and visualising bga results: 1D plots, show one axis only: 1D graphs can be plotted using between.graph and graph1D. between.graph is used for plotting the cases, and required both the co-ordinates of the cases (\$ls) and their centroids (\$li). It accepts an object bga. graph1D can be used to plot either cases (microarrays) or variables (genes) and only requires a vector of coordinates.
绘图和可视化BGA结果：1D图，显示只有一轴：一维图可以使用between.graph和graph1D绘制。 between.graph用于绘图的情况下，需要共同协调的情况下（\ $ LS）和他们的重心（李\ $）。它接受一个对象bga。 graph1D可以用来绘制任何情况下（微阵列）或变量（基因），只需要一个坐标向量。
2D plots: Use plot.bga to plot results from bga. plot.bga calls the functions plotarrays to draw an xy plot of cases (\$ls). plotgenes, is used to draw an xy plot of the variables (genes). plotgenes, is used to draw an xy plot of the variables (genes).
2D绘图：使用plot.bgabga绘制结果。 plot.bga调用功能plotarrays绘制XY图的情况下（LS \ $）。 plotgenes，用于绘制XY绘图的变量（基因）。 plotgenes，用于绘制XY绘图的变量（基因）。
3D plots: 3D graphs can be generated using do3D and html3D. html3D produces a web page in which a 3D plot can be interactively rotated, zoomed, and in which classes or groups of cases can be easily highlighted.
使用do3D和html3D3D绘图：可以生成三维图形。 html3D产生一个网页，其中一个三维图可以交互旋转，放大，并在其中类或群体的情况下，可以很容易地突出。
Analysis of the distribution of variance among axes:
轴间的分布的方差分析：
It is important to know which cases (microarray samples) are discriminated by the axes. The number of axes or principal components from a bga will equal the number of classes - 1, that is length(levels(classvec))-1.
重要的是知道哪些情况（芯片样品）轴歧视。轴或主要部件从一个bga数量将等于the number of classes - 1，即长度（水平（classvec））-1。
The distribution of variance among axes is described in the eigenvalues (\$eig) of the bga analysis. These can be visualised using a scree plot, using scatterutil.eigen as it done in plot.bga. It is also useful to visualise the principal components from a using a bga or principal components analysis dudi.pca, or correspondence analysis dudi.coa using a heatmap. In MADE4 the function heatplot will plot a heatmap with nicer default colours.
bga分析的特征值（\ $ EIG）中所述的轴间的分布差异。这些都可以可视化使用卵石的图，使用scatterutil.eigenplot.bga。使用bga或主要成分分析dudi.pca，或信件的dudi.coa用热图分析可视化的主要组成部分，它也是有用的。在MADE4的功能heatplot将1热图绘制更好的默认颜色。
Extracting list of top variables (genes):
提取列表顶部的变量（基因）：
Use topgenes to get list of variables or cases at the ends of axes. It will return a list of the top n variables (by default n=5) at the positive, negative or both ends of an axes. sumstats can be used to return the angle (slope) and distance from the origin of a list of coordinates.
使用topgenes得到变量或情况列表，在轴的两端。它会返回前n个变量的列表（默认n = 5）在一个轴的正面，负面或两者两端。 sumstats可以用来返回原点的坐标列表的角度（坡度）和距离。
For more details see Culhane et al., 2002 and http://bioinf.ucd.ie/research/BGA.
详细内容见Culhane等人，2002年和http://bioinf.ucd.ie/research/BGA。
值----------Value----------
A list with a class bga containing:
一类bga含名单：
参数：ord
Results of initial ordination. A list of class "dudi" (see dudi )
初步协调的结果。一个类“dudi”名单（见dudi）
参数：bet
Results of between group analysis. A list of class "dudi" (see dudi), "between" (see between)
组间分析的结果。类的“dudi”（见dudi），“之间”（见between）名单
参数：fac
The input classvec, the factor or vector which described the classes in the input dataset
在的输入classvec，factor或vector中描述的输入数据集类
作者（S）----------Author(s)----------
Aedin Culhane
参考文献----------References----------
<h3>See Also</h3> See Also <code>bga</code>, <code>suppl</code>, <code>suppl.bga</code>, <code>between</code>,
举例----------Examples----------
data(khan)
if (require(ade4, quiet = TRUE)) {
khan.bga<-bga(khan$train, classvec=khan$train.classes)
}
khan.bga
plot(khan.bga, genelabels=khan$annotation$Symbol)
# Provide a view of the principal components (axes) of the bga [提供的主要组成部分的观点的BGA（轴）]
heatplot(khan.bga$bet$ls, dend="none")
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 00:00:26
