GlobalAncova(GlobalAncova)
GlobalAncova()所属R语言包：GlobalAncova
Global test for differential gene expression
全球差异表达基因测试
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computation of a F-test for the association between expression values and clinical entities. In many cases a two way layout with gene and a dichotomous group as factors will be considered. However, adjustment for other covariates and the analysis of arbitrary clinical variables, interactions, gene co-expression, time series data and so on is also possible. The test is carried out by comparison of corresponding linear models via the extra sum of squares principle. Corresponding p-values, permutation p-values and/or asymptotic p-values are given.
计算一个表达式的值和临床实体之间的关联的F-检验。在许多情况下，双向布局与基因和一个二元组的因素将被考虑。然而，调整其他变项的任意临床变量的分析，相互作用，基因共表达，时间序列数据等也是可能的。通过最小二乘原理的一笔额外的测试进行相应的线性模型的比较。给出相应的p值，置换p值和/或渐近p-值。
There are three possible ways of using GlobalAncova. The general way is to define formulas for the full and reduced model, respectively, where the formula terms correspond to variables in model.dat. An alternative is to specify the full model and the name of the model terms that shall be tested regarding differential expression. In order to make this layout compatible with the function call in the first version of the package there is also a method where simply a group variable (and possibly covariate information) has to be given. This is maybe the easiest usage in cases where no 'special' effects like e.g. interactions are of interest.
使用GlobalAncova有三种可能的方式。一般的方法是定义公式，为全面和简化模型，公式计算对应变量model.dat。另一种方法是指定完整的模型和模型方面的差异表达方面应测试的名称。为了使这种布局在包的第一个版本的函数调用兼容也有方法给予简单的一组变量（可能协信息）。这也许是最简单的情况下，使用例如像没有特殊的影响相互作用的利益。
用法----------Usage----------
## S4 method for signature 'matrix,formula,formula,ANY,missing,missing,missing'
GlobalAncova(xx, formula.full, formula.red, model.dat,
test.genes, method = c("permutation","approx","both","Fstat"), perm = 10000, max.group.size = 2500, eps = 1e-16, acc = 50)
## S4 method for signature 'matrix,formula,missing,ANY,missing,missing,character'
GlobalAncova(xx, formula.full, model.dat,test.terms,
test.genes, method = c("permutation","approx","both","Fstat"), perm = 10000, max.group.size = 2500, eps = 1e-16, acc = 50)
## S4 method for signature 'matrix,missing,missing,missing,ANY,ANY,missing'
GlobalAncova(xx, group, covars = NULL,
test.genes, method = c("permutation","approx","both","Fstat"), perm = 10000, max.group.size = 2500, eps = 1e-16, acc = 50)
参数----------Arguments----------
参数：xx
Matrix of gene expression data, where columns correspond to samples and rows to genes. The data should be properly normalized beforehand (and log- or otherwise transformed). Missing values are not allowed. Gene and sample names can be included as the row and column names of xx.
基因表达数据矩阵，列对应的基因样本和行。数据应妥善事先标准化（log或以其他方式转化）。遗漏值是不允许的。基因和样本的名称，可以包含作为xx行和列的名称。
参数：formula.full
Model formula for the full model.
整个模型的模型公式。
参数：formula.red
Model formula for the reduced model (that does not contain the terms of interest.)
减少模型的模型公式（不包含权益的条款。）
参数：model.dat
Data frame that contains all the variable information for each sample.
数据框包含每个样品的所有变量的信息。
参数：group
Vector with the group membership information.
向量组成员信息。
参数：covars
Vector or matrix which contains the covariate information for each sample.
向量或矩阵，其中包含了每个样品的协信息。
参数：test.terms
Character vector that contains names of the terms of interest.
特征向量包含利益的条款的名称。
参数：test.genes
Vector of gene names or a list where each element is a vector of gene names.
向量的基因名称或一个列表，其中每个元素都是一个向量基因名称。
参数：method
p-values can be calculated permutation-based ("permutation") or by means of an approximation for a mixture of chi-square distributions ("approx"). Both p-values are provided when specifying method = "both". With option "Fstat" only the global F-statistics are returned without p-values or further information.
p值可以计算出排列为基础的（"permutation"）或近似的卡方分布的混合物（"approx"）。提供指定method = "both"时均P-值。选项"Fstat"只有全球的F-统计返回无p值或进一步的信息。
参数：perm
Number of permutations to be used for the permutation approach. The default is 10,000.
数将用于置换的方式排列。默认值是10,000。
参数：max.group.size
Maximum size of a gene set for which the asymptotic p-value is calculated. For bigger gene sets the permutation approach is used.
渐近p值计算基因组的最大尺寸。设置更大的基因置换的方式使用。
参数：eps
Resolution of the asymptotic p-value.
渐近p值的决议案。
参数：acc
Accuracy parameter needed for the approximation. Higher values indicate higher accuracy.
需要的逼近精度参数。值越高，表明较高的准确性。
值----------Value----------
If test.genes = NULL a list with components
如果test.genes = NULL的组件列表
参数：effect
Name(s) of the tested effect(s)
（S）的测试效果（S）
参数：ANOVA
ANOVA table
ANOVA表
参数：test.result
F-value, theoretical p-value, permutation-based and/or asymptotic p-value
F值，理论P-值，置换和/或渐近p值
参数：terms
Names of all model terms
所有模型条款的名称
If a collection of gene sets is provided in test.genes a matrix is returned whose columns show the number of genes, value of the F-statistic, theoretical p-value, permutation-based and/or asymptotic p-value for each of the gene sets.
如果一个基因组的集合提供了test.genes返回一个矩阵其列显示每个基因的数目，F统计值，p值理论，置换型和/或渐近p值基因组。
方法----------Methods----------
covars = "missing", test.terms = "missing"</dt> In this method, besides the expression matrix xx, model formulas for the full and reduced model and a data frame model.dat specifying corresponding model terms have to be given. Terms that are included in the full but not in the reduced model are those whose association with differential expression will be tested. The arguments group, covars and test.terms are '"missing"'
covars =“失踪”，test.terms =“失踪”在这种方法中，除了表达矩阵xx，完整和简化模型的模型公式和数据框</ DT>model.dat指定相应的模型方面给予。在全包括，但不是在减少模型的条款，其差异表达的关系将受到考验。的论点group，covars和test.terms是“失踪”
covars = "missing", test.terms = "character"</dt> In this method, besides the expression matrix xx, a model formula for the full model and a data frame model.dat specifying corresponding model terms are required. The character argument test.terms names the terms of interest whose association with differential expression will be tested. The basic idea behind this method is that one can select single terms, possibly from the list of terms provided by previous GlobalAncova output, and test them without having to specify each time a model formula for the reduced model. The arguments formula.red, group and covars are '"missing"'
covars =“失踪”，test.terms在此方法中，除了表达矩阵</ DT> =“字符”xx，一个完整的模型的模型公式和数据框model.dat指定相应的模型而言是必需的。字符参数test.terms命名权益的条款，其差异表达的关系将受到考验。这种方法背后的基本想法是，人们可以选择单一的条款，可能从以前的GlobalAncova输出规定的名单，他们无需为减少模型的模型公式来指定每次测试。的论点formula.red，group和covars是“失踪”
group = "ANY", covars = "ANY", test.terms = "missing"</dt> Besides the expression matrix xx a clinical variable group is required. Covariate adjustment is possible via the argument covars but more complex models have to be specified with the methods described above. This method emulates the function call in the first version of the package. The arguments formula.full, formula.red, model.dat and
除了表达矩阵组=“任何”，covars =“任何”，test.terms =“失踪”</ DT>xx临床变量group需要。协变量调整是可能通过参数covars但更复杂的模型必须与上面描述的方法指定。这种方法模拟包的第一个版本的功能调用。参数formula.full，formula.red，model.dat“
注意----------Note----------
This work was supported by the NGFN project 01 GR 0459, BMBF, Germany.
这项工作是NGFN项目01的GR 0459，BMBF的，德国的支持。
作者（S）----------Author(s)----------
Reinhard Meister <a href="mailto:meister@tfh-berlin.de">meister@tfh-berlin.de</a><br>
Ulrich Mansmann <a href="mailto:mansmann@ibe.med.uni-muenchen.de">mansmann@ibe.med.uni-muenchen.de</a><br>
Manuela Hummel <a href="mailto:hummel@ibe.med.uni-muenchen.de">hummel@ibe.med.uni-muenchen.de</a> <br>
with contributions from Sven Knueppel
参考文献----------References----------
参见----------See Also----------
Plot.genes, Plot.subjects, GlobalAncova.closed, GAGO, GlobalAncova.decomp
Plot.genes，Plot.subjects，GlobalAncova.closed，GAGO，GlobalAncova.decomp
举例----------Examples----------
data(vantVeer)
data(phenodata)
data(pathways)
GlobalAncova(xx = vantVeer, formula.full = ~metastases + ERstatus, formula.red = ~ERstatus, model.dat = phenodata, test.genes=pathways[1], method="both", perm = 100)
GlobalAncova(xx = vantVeer, formula.full = ~metastases + ERstatus, test.terms = "metastases", model.dat = phenodata, test.genes=pathways[1], method="both", perm = 100)
GlobalAncova(xx = vantVeer, group = phenodata$metastases, covars = phenodata$ERstatus, test.genes=pathways[1], method="both", perm = 100)
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。
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发表于 2012-2-25 20:40:48
