Literature DB >> 18450812

A correction for estimating error when using the Local Pooled Error Statistical Test.

Carl Murie1, Robert Nadon.   

Abstract

UNLABELLED: Jain et al. introduced the Local Pooled Error (LPE) statistical test designed for use with small sample size microarray gene-expression data. Based on an asymptotic proof, the test multiplicatively adjusts the standard error for a test of differences between two classes of observations by pi/2 due to the use of medians rather than means as measures of central tendency. The adjustment is upwardly biased at small sample sizes, however, producing fewer than expected small P-values with a consequent loss of statistical power. We present an empirical correction to the adjustment factor which removes the bias and produces theoretically expected P-values when distributional assumptions are met. Our adjusted LPE measure should prove useful to ongoing methodological studies designed to improve the LPE's; performance for microarray and proteomics applications and for future work for other high-throughput biotechnologies. AVAILABILITY: The software is implemented in the R language and can be downloaded from the Bioconductor project website (http://www.bioconductor.org).

Entities:  

Mesh:

Year:  2008        PMID: 18450812     DOI: 10.1093/bioinformatics/btn211

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  3 in total

1.  Ets-1 regulates energy metabolism in cancer cells.

Authors:  Meghan L Verschoor; Leigh A Wilson; Chris P Verschoor; Gurmit Singh
Journal:  PLoS One       Date:  2010-10-22       Impact factor: 3.240

2.  Transcriptome comparison and gene coexpression network analysis provide a systems view of citrus response to 'Candidatus Liberibacter asiaticus' infection.

Authors:  Zhi-Liang Zheng; Yihong Zhao
Journal:  BMC Genomics       Date:  2013-01-16       Impact factor: 3.969

3.  Comparison of small n statistical tests of differential expression applied to microarrays.

Authors:  Carl Murie; Owen Woody; Anna Y Lee; Robert Nadon
Journal:  BMC Bioinformatics       Date:  2009-02-03       Impact factor: 3.169

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.