title: Feature extraction and normalization algorithms for high-density oligonucleotide gene expression array data.
abstract: 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.
authors.affiliation: Department of Biomathematics, University of California, Los Angeles, California, USA. eschadt@rosetta.org
authors.forename: E E
authors.initials: EE
authors.lastname: Schadt
authors.forename: C
authors.initials: C
authors.lastname: Li
authors.forename: B
authors.initials: B
authors.lastname: Ellis
authors.forename: W H
authors.initials: WH
authors.lastname: Wong
mesh_terms: D000465:Algorithms; D020869:Gene Expression Profiling / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software