GenePicker: Replicate analysis of Affymetrix gene expression microarrays

Giacomo Finocchiaro, Paola Parise, Simone P. Minardi, Myriam Alcalay, Heiko Müller

Research output: Contribution to journalArticlepeer-review

Abstract

Summary: GenePicker allows efficient analysis of Affymetrix gene expression data performed in replicate, through definition of analysis schemes, data normalization, t-test/ANOVA, Change-Fold Change-analysis and yields lists of differentially expressed genes with high confidence. Comparison of noise and signal analysis schemes allows determining a signal-to-noise ratio in a given experiment. Change Call, Fold Change and Signal mean ratios are used in the analysis. While each parameter alone yields gene lists that contain up to 30% false positives, the combination of these parameters nearly eliminates the false positives as verified by northern blotting, quantitative PCR in numerous independent experiments as well as by the analysis of spike-in data.

Original languageEnglish
Pages (from-to)3670-3672
Number of pages3
JournalBioinformatics
Volume20
Issue number18
DOIs
Publication statusPublished - Dec 12 2004

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Computer Science Applications
  • Computational Theory and Mathematics

Fingerprint Dive into the research topics of 'GenePicker: Replicate analysis of Affymetrix gene expression microarrays'. Together they form a unique fingerprint.

Cite this