SHIP-package(SHIP)
SHIP-package()所属R语言包:SHIP
SHrinkage covariance Incorporating Prior knowledge
结合先验知识的收缩协方差
译者:生物统计家园网 机器人LoveR
描述----------Description----------
The SHIP-package implements the shrinkage estimator of a covariance matrix given any covariance target, such as described by Schaefer and Strimmer in 2005. In addition, it proposes several targets based on biological knowledge extracted from the public database KEGG.
船舶包实现任何协方差目标,如由Schaefer和Strimmer在2005年的协方差矩阵估计的收缩。此外,从公共数据库KEGG中提取的生物知识的基础上提出了几个目标。
Details
详细信息----------Details----------
To use the shrinkage estimator, one should just have at hand a data set in the form of a n x p matrix, and a covariance target.
要使用的收缩估计,应该只具有在手在n x p矩阵,和协方差目标的形式的一个数据集。
If one wishes to use the proposed targets, the data set should be compatible with KEGG, i.e. it should be possible to extract for each gene the pathways it belongs to. This information, for example, can be found in libraries such as hgu133plus2.db.
如果你希望使用建议的目标,应该是数据集与KEGG兼容的,也就是说,它应该是可以提取的每个基因的途径,它属于。信息,例如,可以发现如hgu133plus2.db的图书馆。
(作者)----------Author(s)----------
Monika Jelizarow and Vincent Guillemot
参考文献----------References----------
J. Schaefer and K. Strimmer, 2005. A shrinkage approach to large-scale covariance matrix estimation and implications for functional genomics. Statist. Appl. Genet. Mol. Biol. 4:32.
M. Jelizarow, V. Guillemot, A. Tenenhaus, K. Strimmer, A.-L. Boulesteix, 2010. Over-optimism in bioinformatics: an illustration. Bioinformatics. Accepted. </ul>
实例----------Examples----------
# A short example on a toy dataset[一个简短的例子在玩具数据集]
# require(SHIP)[要求(SHIP)]
data(expl)
attach(expl)
sig1 <- shrink.estim(x,targetD(x))
sig2 <- shrink.estim(x,targetF(x))
sig3 <- shrink.estim(x,targetCor(x,genegroups))
sig4 <- shrink.estim(x,targetG(x,genegroups))
paste(sig1[[2]],collapse=" ")
paste(sig2[[2]],collapse=" ")
paste(sig3[[2]],collapse=" ")
paste(sig4[[2]],collapse=" ")
## Not run: [#不运行:]
# Example on how to get the gene groups lists[例如在如何获得基因组列表]
require(hgu95av2.db)
# e.g. we have some interesting gene names :[例如我们有一些有趣的基因的名称:]
vec <- c("MYC","ID2","PTGER4","ATF4","FGFR1","MET","HLA-DRB6")
# we then want to convert them into Probe Sets[然后,我们想将它们转换成探针组]
symb <- as.list(hgu95av2SYMBOL)
pbsets <- names(symb[unlist(sapply(vec,function(x,l) which(l==x)[1],symb))])
# Probe Sets which are themselves converted into a gene groups list[它们本身转化为一个基因组“列表中的探针组]
genegroups <- as.list(hgu95av2PATH)[pbsets]
## End(Not run)[#(不执行)]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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