copaPerm(copa)
copaPerm()所属R语言包：copa
Measure Significance of COPA by Permutation
COPA的在置换措施的意义
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function can be used to determine the significance of the results that one gets from running copa on a particular dataset, based on permuting the class assignments.
此功能可用于确定运行得到的结果的意义copa在一个特定的数据集，基于置换的课堂作业。
用法----------Usage----------
copaPerm(object, copa, outlier.num, gene.pairs, B = 100, pval = FALSE, verbose = TRUE)
参数----------Arguments----------
参数：object
An ExpressionSet, or a matrix or data.frame.
ExpressionSet，或矩阵或data.frame。
参数：copa
An object of class 'copa', produced by running copa on a set of microarray data.
一个类杯运行copa一组微阵列数据所产生的对象。
参数：outlier.num
The number of outliers to test for. See details for more information
的离群测试。详情请参阅有关详细信息，
参数：gene.pairs
The number of gene pairs to test for. See details for more information
基因对数测试。详情请参阅有关详细信息，
参数：B
The number of permutations to perform. Defaults to 100. This may be too many for interactive use.
排列数执行。默认为100。这可能是交互使用太多。
参数：pval
Boolean. Output an estimated p-value and false discovery rate? Defaults to FALSE. This result will only be reasonable for large numbers of permutations (500 - 1000). See details.
布尔值。输出估计p值和虚假的发现率？ FALSE默认。这样的结果只会是合理的排列的大量（500 - 1000）。查看详情。
参数：verbose
Boolean. Print out the permutation number at each of 100, 200, etc. Defaults to TRUE
布尔值。打印出置换数量在100，200等默认TRUE
Details
详情----------Details----------
Running copa on a set of microarray data will result in the output of an object of class 'copa', which is a list containing (among other things) an ordered vector that lists the number of mutually exclusive outlier samples for various gene pairs. This vector is ordered from smallest to largest following the assumption that the gene pairs with the most mutually exclusive outliers are probably more likely to be involved in some sort of recurrent fusion.
运行copa微阵列数据集，将导致在输出类杯，这是一个列表，包含（除其他事项外），列出了各种相互排斥的离群样本数的有序向量对象基因对。这个向量被下令从最小到最大后，假设，可能更容易被某种经常性融合基因对最互斥离群。
One can see how many pairs of genes resulted in a given number of outliers by calling tableCopa. One may then want to determine how significant a certain number of pairs is (e.g., how likely is it to get that many pairs if there is no recurrent fusion occuring). The most straightforward way to estimate the significance of a given result is to repeatedly permute the classlabels and see how many times one gets a result as large or larger than what was observed.
人们可以看到对许多基因如何在给定数量的离群导致调用tableCopa。然后要确定对若干重要的是如何（例如，如何可能是它得到许多对，如果没有经常性的融合易出现）。最简单的方法来估计一个给定的结果的意义是多次置位classlabels和看多少次得到一个或大或大于观察的结果。
Technically speaking, to get a reasonable estimate of significance and a false discovery rate, one would need to permute 500 - 1000 times. However, this can take an inordinate amount of time (best left for an overnight run). To get a quick idea of significance, one could simply permute maybe 10 times (with pval = FALSE) to see how likely it is to get a certain number of outliers.
从技术上来讲，得到一个合理的意义和虚假的发现率估计，需要重排500 - 1000倍。然而，这可能需要大量时间（最好留一个通宵运行）。得到一个快速的意义的想法，可以简单地置位也许10倍（pval的= FALSE）得到一个离群一定的数量的可能性有多大。
值----------Value----------
参数：out
A vector listing the number of gene pairs with at least as many outliers as 'num.outlier'.
列出一个向量与基因对数至少多达“num.outlier离群。
参数：p.value
A permuted p-value, only output if pval = TRUE. Note that the size of the p-value is determined by both the number of outliers >= 'num.outlier' as well as the number of permutations, so too few permutations may result in a p-value that doesn't look very significant even if it is.
一个置换p值，如果pval的= TRUE，只输出。注意，p值的大小确定的离群> =num.outlier以及排列的数量，所以太少排列可能会导致在一个P-值不看起来很显着，即使它是。
参数：fdr
The expected number of gene pairs with at least as many outliers as 'num.outlier'. This can be converted to a %FDR by dividing by the observed value.
预计的基因对数至少多达“num.outlier离群。这可以转换为％FDR除以观测值。
作者（S）----------Author(s)----------
James W. MacDonald
参考文献----------References----------
factor genes in prostate cancer. Science. 2005 Oct 28;310(5748):644-8.
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 15:48:43
