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Feature extraction and normalization algorithms for high‐density oligonucleotide gene expression array data
Author(s) -
Schadt Eric E.,
Li Cheng,
Ellis Byron,
Wong Wing H.
Publication year - 2001
Publication title -
journal of cellular biochemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.028
H-Index - 165
eISSN - 1097-4644
pISSN - 0730-2312
DOI - 10.1002/jcb.10073
Subject(s) - normalization (sociology) , database normalization , computer science , feature extraction , oligonucleotide , algorithm , pattern recognition (psychology) , data mining , artificial intelligence , gene , biology , genetics , sociology , anthropology
Algorithms for performing feature extraction and normalization on high‐density oligonucleotide gene expression arrays, have not been fully explored, and the impact these algorithms have on the downstream analysis is not well understood. Advances in such low‐level analysis methods are essential to increase the sensitivity and specificity of detecting whether genes are present and/or differentially expressed. We have developed and implemented a number of algorithms for the analysis of expression array data in a software application, the DNA‐Chip Analyzer (dChip). In this report, we describe the algorithms for feature extraction and normalization, and present validation data and comparison results with some of the algorithms currently in use. J. Cell. Biochem. Suppl. 37: 120–125, 2001. © 2002 Wiley‐Liss, Inc.