RankingEbam(GeneSelector)
RankingEbam()所属R语言包：GeneSelector
Ranking based on the empirical Bayes approach of Efron et al. (2001)
埃弗龙等人的经验Bayes方法的基础上的排名。 （2001）
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The approach of Efron et al. (2001) is based on a mixture model for two subpopulations: genes that are differentially expressed and those not. The posterior probability for differential expression is used to obtain a ranking. The function described below is merely a wrapper for the function z.ebam from the package siggenes.<br> For S4 method information, see RankingEbam-methods.
埃弗龙等人的做法。 （2001年）的基础上为两个亚群混合模型：基因差异表达和那些不。用于差异表达的后验概率获得排名。下文所述的功能仅仅是一个功能z.ebam包siggenesS4方法信息参考的包装，看到RankingEbam方法。
用法----------Usage----------
RankingEbam(x, y, type = c("unpaired", "paired", "onesample"), gene.names = NULL, ...)
参数----------Arguments----------
参数：x
A matrix of gene expression values with rows corresponding to genes and columns corresponding to observations or alternatively an object of class ExpressionSet.<br> If type = "paired", the first half of the columns corresponds to the first measurements and the second half to the second ones. For instance, if there are 10 observations, each measured twice, stored in an expression matrix expr, then expr[,1] is paired with expr[,11], expr[,2] with expr[,12], and so on.
一个matrix基因表达值与相应的基因和相应的意见，或者一个对象类ExpressionSet。参考列的行，如果type = "paired"上半年，列对应第一次测量和下半年第二。例如，如果有10个观测，每个测两次，表达矩阵expr，则expr[,1]expr[,11]，expr[,2]搭配expr[,12]存储 ，等等。
参数：y
If x is a matrix, then y may be a numeric vector or a factor with at most two levels.<br> If x is an ExpressionSet, then y is a character specifying the phenotype variable in the output from pData.<br> If type = "paired", take care that the coding is analogously to the requirement concerning x.
x如果是一个矩阵，然后y可能是一个numeric矢量或在大多数两个级别的一个因素。参考如果x是ExpressionSet ，然后y是pData。参考型变量指定输出的字符，如果type = "paired"，照顾编码类似的要求是关于x 。
参数：type
"unpaired":two-sample test.
“未成”：两样本测试。
"paired":paired test. Take care that the coding of y is correct (s. above)
“配对”配对测试。照顾y编码是正确的（与上述）
"onesample":y has only one level. Test whether the true mean is different from zero.
“onesample”：y只有一个级别。测试是否是真正的平均异于零。
参数：gene.names
An optional vector of gene names.
一个基因名称可选的向量。
参数：...
Further arguments passed to the function z.ebam. Can be used to influence the fudge factor to the stabilize the variance. Currently, the 90 percent quantile is used.
进一步的参数传递给函数z.ebam。可用于软糖因素的影响稳定的变异。目前，90％的分量。
Details
详情----------Details----------
To find a better value for the fudge factor, the function find.a0 (package siggenes) can be used.
蒙混因素找到一个更好的价值，功能find.a0（包siggenes）可以使用。
值----------Value----------
An object of class GeneRanking.
对象类GeneRanking。
注意----------Note----------
P-values are not computed - the statistic is
P值计算 - 统计
作者（S）----------Author(s)----------
Martin Slawski <br>
Anne-Laure Boulesteix
参考文献----------References----------
Empirical Bayes Analysis of a Microarray Experiment. Journal of the American Statistical Association, 96, 1151-1160.
Comparison of the Empirical Bayes and the Significance Analysis of Microarrays.
参见----------See Also----------
RepeatRanking, RankingTstat, RankingFC, RankingWelchT, RankingWilcoxon, RankingBaldiLong, RankingFoxDimmic, RankingLimma, RankingWilcEbam, RankingSam, RankingShrinkageT, RankingSoftthresholdT,
RepeatRanking，RankingTstat，RankingFC，RankingWelchT，RankingWilcoxon，RankingBaldiLong，RankingFoxDimmic，RankingLimma，RankingWilcEbam，RankingSam，RankingShrinkageT，RankingSoftthresholdT
举例----------Examples----------
### Load toy gene expression data[＃负载玩具基因表达数据]
data(toydata)
### class labels[＃＃类的标签]
yy <- toydata[1,]
### gene expression[＃＃基因表达]
xx <- toydata[-1,]
### run RankingEbam[＃运行RankingEbam]
Ebam <- RankingEbam(xx, yy, type="unpaired")
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 19:03:31
