A1 Refereed original research article in a scientific journal
Integrating probe-level expression changes across generations of Affymetrix arrays
Authors: Elo LL, Lahti L, Skottman H, Kylaniemi M, Lahesmaa R, Aittokallio T
Publisher: OXFORD UNIV PRESS
Publication year: 2005
Journal: Nucleic Acids Research
Journal name in source: NUCLEIC ACIDS RESEARCH
Journal acronym: NUCLEIC ACIDS RES
Article number: ARTN e193
Volume: 33
Issue: 22
Number of pages: 10
ISSN: 0305-1048
DOI: https://doi.org/10.1093/nar/gni193
Abstract
There is an urgent need for bioinformatic methods that allow integrative analysis of multiple microarray data sets. While previous studies have mainly concentrated on reproducibility of gene expression levels within or between different platforms, we propose a novel meta-analytic method that takes into account the vast amount of available probe-level information to combine the expression changes across different studies. We first show that the comparability of relative expression changes and the consistency of differentially expressed genes between different Affymetrix array generations can be considerably improved by determining the expression changes at the probe-level and by considering the latest information on probe-level sequence matching instead of the probe annotations provided by the manufacturer. With the improved probe-level expression change estimates, data from different generations of Affymetrix arrays can be combined more effectively. This will allow for the full exploitation of existing results when designing and analyzing new experiments.
There is an urgent need for bioinformatic methods that allow integrative analysis of multiple microarray data sets. While previous studies have mainly concentrated on reproducibility of gene expression levels within or between different platforms, we propose a novel meta-analytic method that takes into account the vast amount of available probe-level information to combine the expression changes across different studies. We first show that the comparability of relative expression changes and the consistency of differentially expressed genes between different Affymetrix array generations can be considerably improved by determining the expression changes at the probe-level and by considering the latest information on probe-level sequence matching instead of the probe annotations provided by the manufacturer. With the improved probe-level expression change estimates, data from different generations of Affymetrix arrays can be combined more effectively. This will allow for the full exploitation of existing results when designing and analyzing new experiments.
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