GlobalAncova.closed(GlobalAncova)
GlobalAncova.closed()所属R语言包：GlobalAncova
Closed testing procedure for testing several groups of genes using GlobalAncova
封闭测试使用GlobalAncova几个基因组的测试程序
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computation of a closed testing procedure for several groups of genes, e.g. pathways, as an alternative of correcting for multiple testing. Starting from the pathways of interest a family of null hypotheses is created that is closed under intersection. Each null hypothesis can be rejected at a given level if it is rejected along with all hypotheses included in it.
几组基因，如计算一个封闭的测试程序途径，作为替代纠正多个测试。开始从利益的途径，根据路口封闭的家庭创建一个空假说。每个拒绝零假设，可以在一个给定的水平，如果被拒绝，它包括所有假设。
There are three possible ways of using GlobalAncova. Also GlobalAncova.closed can be invoked with these three alternatives.
使用GlobalAncova有三种可能的方式。 GlobalAncova.closed可以调用这三个替代品。
用法----------Usage----------
## S4 method for signature 'matrix,list,formula,formula,ANY,missing,missing,missing'
GlobalAncova.closed(xx, test.genes,
formula.full, formula.red, model.dat, previous.test, level, method = c("permutation","approx"), perm = 10000,
max.group.size = 2500, eps = 1e-16, acc = 50)
## S4 method for signature 'matrix,list,formula,missing,ANY,missing,missing,character'
GlobalAncova.closed(xx, test.genes,
formula.full, model.dat, test.terms, previous.test, level, method = c("permutation","approx"), perm = 10000,
max.group.size = 2500, eps = 1e-16, acc = 50)
## S4 method for signature 'matrix,list,missing,missing,missing,ANY,ANY,missing'
GlobalAncova.closed(xx, test.genes,
group, covars = NULL, previous.test, level, method = c("permutation","approx"), 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：test.genes
A list of named pathways that shall be tested, each containing vectors of gene names.
一个名为途径应测试的名单，每个基因名称含有向量。
参数：previous.test
The output of a call to GlobalAncova with specified option test.genes according to the pathways of interest (optional).
调用的输出GlobalAncova指定的选项test.genes根据利息（可选）的途径。
参数：level
The global level of significance of the testing procedure.
全球一级的测试过程中具有重要意义。
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).
为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：method
Raw p-values can be calculated permutation-based ("permutation") or by means of an approximation ("approx").
原P-值可以计算为基础的置换（"permutation"）（"approx"）或近似的手段。
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----------
A list with components
与组件列表
参数：new.data
Family of null hypotheses (vectors of genes to be tested simultaneously with GlobalAncova).
虚无假设（基因的向量，同时进行测试与GlobalAncova）的家庭。
参数：test.results
Test results for each pathway of interest and all hypotheses included in it.
包括在每个通路的利益和所有假设的测试结果。
参数：significant
Names of the significant pathways.
名称的重要途径。
参数：not.significant
Names of the non significant pathways.
名称非重要途径。
方法----------Methods----------
xx = "matrix", test.genes="list", formula.full = "formula", formula.red = "formula", model.dat = "ANY", group = "missing", covars = "missing", test.terms = "missing" In this method, besides the expression matrix xx and the list of gene groups test.genes, 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"'
XX =“矩阵”，test.genes =“名单”，formula.full =“公式”，formula.red =“的公式”，model.dat =“任何”，组=“失踪” covars =xx完整和简化模型，模型的公式和“失踪”，test.terms =“失踪”在这种方法中，除了表达矩阵test.genes和基因组名单数据框model.dat指定相应的模型计算得到。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”
xx = "matrix", test.genes="list", formula.full = "formula", formula.red = "missing", model.dat = "ANY", group = "missing", covars = "missing", test.terms = "character" In this method, besides the expression matrix xx and the list of gene groups test.genes, 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 arguments formula.red, group and covars are '"missing"'
XX =“矩阵”，test.genes =“名单”，formula.full =“的公式”，formula.red =“失踪”，model.dat =“任何”，组=“失踪” covars =“失踪”，test.terms =“字符”在这种方法中，除了表达基质xx和test.genes，一个完整的模型的模型公式和数据的基因组名单帧model.dat指定相应的模型计算需要。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。的论点formula.red，group和covars是“失踪”
xx = "matrix", test.genes="list", formula.full = "missing", formula.red = "missing", model.dat = "missing", group = "ANY", covars = "ANY", test.terms = "missing" Besides the expression matrix xx and the list of gene groups test.genes 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
XX =“矩阵”，test.genes =“名单”，formula.full =“失踪”，formula.red =“失踪”，model.dat =“失踪”，组“任何”， covars =“任何”，test.terms =“失踪”除了表达矩阵xx和基因组名单test.genes临床变量group是必需的。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>
参考文献----------References----------
参见----------See Also----------
GlobalAncova, Plot.genes, Plot.subjects
GlobalAncova，Plot.genes，Plot.subjects
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 20:40:31
