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A Renewed Approach to the Nonparametric Analysis of Replicated Microarray Experiments
Author(s) -
Jung Klaus,
Quast Karsten,
Gannoun Ali,
Urfer Wolfgang
Publication year - 2006
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.200510189
Subject(s) - nonparametric statistics , dna microarray , statistical hypothesis testing , r package , microarray , computer science , statistical analysis , multiple comparisons problem , gene chip analysis , microarray analysis techniques , computational biology , data mining , statistics , biology , gene , mathematics , gene expression , genetics
DNA-microarrays find broad employment in biochemical research. This technology allows the monitoring of the expression levels of thousands of genes at the same time. Often, the goal of a microarray study is to find differentially expressed genes in two different types of tissue, for example normal and cancerous. Multiple hypothesis testing is a useful statistical tool for such studies. One approach using multiple hypothesis testing is nonparametric analysis for replicated microarray experiments. In this paper we present an improved version of this method. We also show how p-values are calculated for all significant genes detected with this testing procedure. All algorithms were implemented in an R-package, and instructions on it's use are included. The package can be downloaded at http://www.statistik.unidortmund.de/de/content/einrichtungen/lehrstuehle/personen/jung.html