Fewer permutations, more accurate P-values.
Fewer permutations, more accurate P-values.
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DOI：
10.1093/bioinformatics/btp211
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发表时间：
2009-06-15
期刊：
影响因子：
--
通讯作者：
Shmulevich I
中科院分区：
文献类型：
--
作者：
Knijnenburg TA;Wessels LF;Reinders MJ;Shmulevich I
动机：排列试验已成为评估调查事件的统计显著性的标准工具。统计显著性，用p值表示，计算为至少与原始统计量一样极端的排列值的比例，原始统计量来自非排列数据。这种经验方法将最小可得p值和p值的分辨率直接耦合到排列数上。因此，当要准确估计小的p值时，它要求自己需要非常多的排列。这在计算上是昂贵的，而且通常是不可行的。结果：提出了一种基于尾部近似的p值计算方法。置换值分布的尾部近似为广义Pareto分布。与计算p值的标准经验方法相比，可以通过大幅减少排列数量来获得良好的拟合，从而获得准确的p值估计。可用性：Matlab代码可根据要求从通信作者处获得。补充信息：补充数据可在Bioinformatics在线获取。
Motivation: Permutation tests have become a standard tool to assess the statistical significance of an event under investigation. The statistical significance, as expressed in a P-value, is calculated as the fraction of permutation values that are at least as extreme as the original statistic, which was derived from non-permuted data. This empirical method directly couples both the minimal obtainable P-value and the resolution of the P-value to the number of permutations. Thereby, it imposes upon itself the need for a very large number of permutations when small P-values are to be accurately estimated. This is computationally expensive and often infeasible. Results: A method of computing P-values based on tail approximation is presented. The tail of the distribution of permutation values is approximated by a generalized Pareto distribution. A good fit and thus accurate P-value estimates can be obtained with a drastically reduced number of permutations when compared with the standard empirical way of computing P-values. Availability: The Matlab code can be obtained from the corresponding author on request. Contact: tknijnenburg@systemsbiology.org Supplementary information:Supplementary data are available at Bioinformatics online.
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DOI：
10.1089/cmb.2008.0137
发表时间：
2009-01
期刊：
Journal of computational biology : a journal of computational molecular cell biology
影响因子：
--
作者：
Newberg LA;Lawrence CE
通讯作者：
Lawrence CE
影响因子：
2.5
作者：
HOSKING, JRM;WALLIS, JR
通讯作者：
WALLIS, JR
DOI：
10.1073/pnas.091062498
发表时间：
2001-04-24
影响因子：
11.1
作者：
Tusher, VG;Tibshirani, R;Chu, G
通讯作者：
Chu, G
影响因子：
158.5
作者：
van de Vijver, MJ;He, YD;Bernards, R
通讯作者：
Bernards, R
影响因子：
3
作者：
Keller, Andreas;Backes, Christina;Lenhof, Hans-Peter
通讯作者：
Lenhof, Hans-Peter