How to decide whether small samples comply with an equidistribution.
The decision whether a measured distribution complies with an equidistribution is a central element of many biostatistical methods. High throughput differential expression measurements, for instance, necessitate to judge possible over-representation of genes. The reliability of this judgement, however, is strongly affected when rarely expressed genes are pooled. We propose a method that can be applied to frequency ranked distributions and that yields a simple but efficient criterion to assess the hypothesis of equiprobable expression levels. By applying our technique to surrogate data we exemplify how the decision criterion can differentiate between a true equidistribution and a triangular distribution. The distinction succeeds even for small sample sizes where standard tests of significance (e.g. chi(2)) fail. Our method will have a major impact on several problems of computational biology where rare events baffle a reliable assessment of frequency distributions. The program package is available upon request from the authors.
Pöschel
Thorsten
T
Institut für Biochemie, Humboldt-Universität zu Berlin, Charité, Monbijoustrasse 2, D-10117 Berlin, Germany. thorsten.poeschel@charite.de
Freund
Jan A
JA
D001699:Biometry; D020411:Oligonucleotide Array Sequence Analysis