attract-package(attract)
attract-package()所属R语言包：attract
Methods to find the Gene Expression Modules that Represent the Drivers of Kauffman's Attractor Landscape
找到代表考夫曼的吸引景观驱动的基因表达模块的方法
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This package contains functions used to determine the gene expression modules that represent the drivers of Kauffman's attractor landscape.
这个软件包包含用于确定代表考夫曼的吸引景观司机的基因表达模块的功能。
Details
详情----------Details----------
The method can be summarized in the following key steps: (1) Determine core KEGG pathways that discriminate the most strongly between celltypes or experimental groups of interest (see findAttractors)). (2) Find the different synexpression groups that are present within a core attractor pathway (see findSynexprs). (3) Find sets of genes that show highly similar profiles to the synexpression groups within an attractor pathway module (see findCorrPartners). (4) Test for functional enrichment for each of the synexpression groups to detect any potentially shared biological themes (see calcFuncSynexprs).
该方法可以归纳为以下关键步骤：（1）确定核心KEGG途径歧视利益之间celltypes或实验组的最强烈（见findAttractors)）。 （2）的核心吸引通路内（见findSynexprs的不同synexpression组）。 （3）套基因，表明内吸引通路模块高度相似概况的synexpression组（见findCorrPartners）。 （4）测试功能富集的每个的synexpression组发现任何可能共享的生物主题（见calcFuncSynexprs）。
作者（S）----------Author(s)----------
Jessica Mar <jess@jimmy.harvard.edu>
参考文献----------References----------
Mar JC, Wells CA, Quackenbush J. 2010. Identifying Gene Expression Modules that Represent the Drivers of Kauffman's Attractor Landscape. To Appear. M黮ler F et al. 2008. Regulatory networks define phenotypic classes of human stem cell lines. Nature. 455(7211): 401. Mar JC, Wells CA, Quackenbush J. 2010. Defining an Informativeness Metric for Clustering Gene Expression Data. To Appear.
举例----------Examples----------
## Not run: [＃无法运行：]
data(subset.loring.eset)
attractor.states <- findAttractors(subset.loring.eset, "celltype", nperm=10, annotation="illuminaHumanv1.db")
remove.these.genes <- removeFlatGenes(subset.loring.eset, "celltype", contrasts=NULL, limma.cutoff=0.05)
mapk.syn <- findSynexprs("04010", attractor.states, remove.these.genes)
mapk.cor <- findCorrPartners(mapk.syn, subset.loring.eset, remove.these.genes)
mapk.func <- calcFuncSynexprs(mapk.syn, attractor.states, "CC", annotation="illuminaHumanv1.db")
## End(Not run)[＃结束（不运行）]
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 12:25:05
