enrichment(eisa)
enrichment()所属R语言包：eisa
Enrichment analysis for transcription modules, based on
富集转录模块分析的基础上，
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function performs enrichment analysis for each ISA module separately, comparing it to user-defined categories. It is useful to test against other databases and annotations than the Gene Ontology or KEGG pathways.
执行此功能为每个ISA模块分别富集分析，比较，以用户定义的类别。它是有用的测试比其他数据库和基因本体论或KEGG通路的注释。
用法----------Usage----------
ISAEnrichment (modules, categories, ann = annotation(modules),
features = featureNames(modules), hgCutoff = 0.05,
correction = TRUE, correction.method = "holm")
参数----------Arguments----------
参数：modules
An ISAModules object, a set of ISA modules.
ISAModules对象，一组的ISA模块。
参数：categories
A named list of gene categories. The names of the entries are used as category names. Each entry of the list must be a character vector containing Entrez gene ids.
命名的基因类别列表。参赛作品的名称作为类名称。列表中的每个条目必须是一个字符向量Entrez基因IDS。
参数：ann
Character scalar. The annotation package to be used. By default it is taken from the modules argument.
字符标。注释要使用的包。默认情况下它是取自modules参数。
参数：features
Character vector. The names of the features. By default it is taken from the modules argument.
特征向量。功能的名称。默认情况下它是取自modules参数。
参数：hgCutoff
Numeric scalar. The cutoff value to be used for the enrichment significance. This can be changed later, without recalculating the test.
数字标。截止值将用于充实意义。这是可以改变后，没有重新计算测试。
参数：correction
Logical scalar, whether to perform multiple hypothesis testing correction.
逻辑标量，是否执行多个假设检验校正。
参数：correction.method
Character scalar, the multiple testing correction method to use. Possible values: “holm”, “hochberg”, “hommel”, “bonferroni”, “BH”, “BY”, “fdr”, “none”. See the p.adjust function for details on these.
字符标量，使用多个测试校正方法。可能的值：“冬青”，“hochberg”，“HOMMEL”，“邦弗朗尼”，“波黑”，“”，“FDR”，“无”。见p.adjust这些细节功能。
Details
详情----------Details----------
This function performs enrichment analysis, based on user defined gene labels. It is useful if one want to test ISA modules against databases, other than GO and KEGG.
执行此功能富集分析，根据用户定义的基因标签。如果要测试的ISA模块对数据库，GO及KEGG以外，它是有用的。
The hypergeometric test, a version Fisher's exact test, takes a gene label and a gene set (in our case coming from an ISA module) and asks whether the number of genes in the set labelled by the label is significantly more (or less) than what one would expect by chance.
的超几何试验，1版费舍尔的精确检验，需要1基因的标签和1的基因组（在我们的情况下从1的ISA模块），并询问由标签标记的一套基因的数量是否显著更多（或更少）比什么人会想到一个偶然的机会。
ISAEnrichment performs the hypergeometric test for every module, for all user supplied gene labels. The mapping from the probe ids on the array to Entrez Ids is done using the appropriate chip annotation package.
ISAEnrichment执行每个模块的超几何试验，为所有用户提供的基因标签。从Entrez的IDS阵列探针标识的映射是使用适当的芯片注解包。
ISAEnrichment currently cannot test for under-representation.
ISAEnrichment目前无法测试的代表性不足。
值----------Value----------
A GeneralListHyperGResult object.
一个GeneralListHyperGResult对象。
作者（S）----------Author(s)----------
Gabor Csardi <a href="mailto:Gabor.Csardi@unil.ch">Gabor.Csardi@unil.ch</a>
参考文献----------References----------
analysis of large-scale gene expression data Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Mar;67(3 Pt 1):031902. Epub 2003 Mar 11.
参见----------See Also----------
ISAGO, ISACHR, ISAKEGG and ISAmiRNA for other enrichment calculations.
ISAGO，ISACHR，ISAKEGG和ISAmiRNA其他的富集计算。
The Category package.
Category包。
举例----------Examples----------
data(ALLModulesSmall)
library(hgu95av2.db)
entrez <- unique(unlist(mget(featureNames(ALLModulesSmall), hgu95av2ENTREZID)))
categories <- lapply(letters, function(x) sample(entrez, 100))
names(categories) <- letters
fakeEnrichment1 <- ISAEnrichment(ALLModulesSmall, categories, correction=FALSE)
fakeEnrichment2 <- ISAEnrichment(ALLModulesSmall, categories, correction=TRUE)
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。
|
发表于 2012-2-25 17:12:40
