genas(limma)
genas()所属R语言包：limma
Genuine Association of Gene Expression Profiles
真正协会的基因表达谱
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Calculates biological correlation between two gene expression profiles.
计算两个基因表达谱之间的生物相关。
用法----------Usage----------
genas(fit, coef=c(1,2))
参数----------Arguments----------
参数：fit
an MArrayLM fitted model object produced by lmFit or contrasts.fit and followed by eBayes
其次是一个MArrayLM拟合模型对象lmFit或contrasts.fit“生产eBayes
参数：coef
numeric vector of length 2 to indicate which contrasts/columns in the fit object are to be used
数字矢量的长度为2表示对比/列在合适的对象，要使用
Details
详情----------Details----------
The biological correlation between the true log fold changes of pairs of comparisons is computed. This method is to be applied when multiple groups (such as treatment groups, mutants or knock-outs) are compared back to the same control group.
生物之间的真实记录，比较，对折变化的相关性计算。这种方法被应用时（如治疗组，突变或敲奏）多个团体同对照组比较。
This method is an extension of the empirical Bayes method of limma. It aims to separate the technical correlation, which comes from comparing multiple treatment/mutant/knock-out groups to the same control group, from biological correlation, which is the true correlation of the gene expression profiles between two treatment/mutant/knock-out groups.
这个方法是limma的经验Bayes方法的延伸。它的目的是分离的相关技术，从生物相关性，这是真正的相关基因表达谱之间的两个治疗/突变体/基因敲除，同对照组比较多的治疗/突变体/基因敲除集团组。
The fit object should include only differentially expressed genes. One approach is to calculate the true proportion of differentially expressed genes using convest on the F p-value produced by lmFit. Any reasonable set of genes displaying some degree of differential expression should be adequate.
合适的对象应包括唯一的差异表达基因。一种方法是计算出真实比例的差异表达基因，使用convest在F p值lmFit生产。任何显示某种程度的差异表达基因的合理设置应该足够了。
值----------Value----------
genas produces a list with the following components.
genas产生了以下组件的列表。
参数：technical.correlation
estimate of the technical correlation
技术相关的估计
参数：covariance.matrix
estimate of the covariance matrix from which the biological correlation is obtained
从获得生物相关的协方差矩阵估计
参数：biological.correlation
estimate of the biological correlation
生物相关的估计
参数：deviance
the likelihood ratio test statistic used to test whether the biological correlation is equal to 0
用来测试生物的相关性是否等于0的似然比检验统计
参数：p.value
the p.value associated with deviance
p.value以deviance
作者（S）----------Author(s)----------
Belinda Phipson and Gordon Smyth
参见----------See Also----------
lmFit, eBayes, contrasts.fit
lmFit，eBayes，contrasts.fit
举例----------Examples----------
library(limma)
# Simulate gene expression data,[模拟基因表达数据，]
# 6 microarrays with 100 genes on each array [6有100个基因的微阵列，每个阵列]
set.seed(2004)
y<-matrix(rnorm(600),ncol=6)
# two experimental groups and one control group with two replicates each[两个实验组和两个对照组的复制每个]
group<-factor(c("A","A","B","B","control","control"))
design<-model.matrix(~0+group)
colnames(design)<-c("A","B","control")
# fit a linear model[符合线性模型]
fit<-lmFit(y,design)
contrasts<-makeContrasts(A-control,B-control,levels=design)
fit2<-contrasts.fit(fit,contrasts)
fit2<-eBayes(fit2)
# calculate biological correlation between the gene expression profiles of (A vs control) and (B vs control)[计算生物相关（与控制）的基因表达谱和（乙组与对照组之间）]
genas(fit2)
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。
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发表于 2012-2-25 23:15:01
