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An expression index for Affymetrix GeneChips based on the generalized logarithm
Author(s) -
Lei Zhou,
David M. Rocke
Publication year - 2005
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bti665
Subject(s) - normalization (sociology) , logarithm , cluster analysis , computer science , expression (computer science) , data mining , gene chip analysis , index (typography) , pattern recognition (psychology) , computational biology , artificial intelligence , dna microarray , mathematics , gene expression , biology , genetics , gene , mathematical analysis , sociology , world wide web , anthropology , programming language
Affymetrix GeneChip high-density oligonucleotide arrays interrogate a single transcript using multiple short 25mer probes. Usually, a necessary step in the analysis of experiments using these GeneChips is to summarize each of these probe sets into a single expression index that can then be used for determining differential expression, for classification, for clustering, and for other analyses. In this paper, we propose a new expression index that is competitive with the best existing methods, and superior in many cases. We call this expression index method GLA, for GLog Average, since after normalization at the probe level, we take the mean generalized logarithm of perfect match probes.

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