Adjustments and measures of differential expression for microarray data
Author(s) -
Alexander Tsodikov,
Anikó Szabó,
David A. Jones
Publication year - 2002
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/18.2.251
Subject(s) - categorical variable , computer science , normalization (sociology) , data mining , statistical hypothesis testing , ranking (information retrieval) , microarray analysis techniques , microarray databases , statistics , mathematics , artificial intelligence , machine learning , gene expression , biochemistry , chemistry , sociology , gene , anthropology
Existing analyses of microarray data often incorporate an obscure data normalization procedure applied prior to data analysis. For example, ratios of microarray channels intensities are normalized to have common mean over the set of genes. We made an attempt to understand the meaning of such procedures from the modeling point of view, and to formulate the model assumptions that underlie them. Given a considerable diversity of data adjustment procedures, the question of their performance, comparison and ranking for various microarray experiments was of interest.
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