Detecting differentially expressed genes in multiple tag sampling experiments: comparative evaluation of statistical tests.

Abstract:

:The comparison of several statistical methods currently used for detection of differentially expressed genes was attempted both by a simulation approach and by the analysis of data sets of human expressed sequence tags, obtained from UniGene. In the simulated mixed case, mimicking a situation close to reality, the general chi(2) test was unexpectedly the most efficient in multiple tag sampling experiments, especially when dealing with variations affecting weakly expressed genes. On the other hand, Audic and Claverie's method proved the most efficient for detecting differences in gene expression when dealing with pairwise comparisons. By applying the above methods on UniGene-based data sets concerning two human kidney tumours compared with normal kidney tissue, three novel genes overexpressed in these tumours were identified. Software and additional information on statistical methodologies, simulation approach and data are available at http://telethon.bio.unipd.it/bioinfo/IDEG6/.

journal_name

Hum Mol Genet

journal_title

Human molecular genetics

authors

Romualdi C,Bortoluzzi S,Danieli GA

doi

10.1093/hmg/10.19.2133

subject

Has Abstract

pub_date

2001-09-15 00:00:00

pages

2133-41

issue

19

eissn

0964-6906

issn

1460-2083

journal_volume

10

pub_type

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