title: Detection of genes with tissue-specific expression patterns using Akaike's information criterion procedure.
abstract: We applied a method based on Akaike's information criterion (AIC) to detect genes whose expression profile is considerably different in some tissue(s) than in others. Such observations are detected as outliers, and the method we used was originally developed to detect outliers. The main advantage of the method is that objective decisions are possible because the procedure is independent of a significance level. We applied the method to 48 expression ratios corresponding to various tissues in each of 14,610 clones obtained from the RIKEN Expression Array Database (READ; http://read.gsc.riken.go.jp). As a result, for several tissues (e.g., muscle, heart, and tongue tissues that contain similar cell types) we objectively obtained specific clones without any "thresholding." Our study demonstrates the feasibility of the method for detecting tissue-specific gene expression patterns.
authors.affiliation: Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo 135-0064 Japan.
authors.forename: Koji
authors.initials: K
authors.lastname: Kadota
authors.forename: Shin-Ichiro
authors.initials: S
authors.lastname: Nishimura
authors.forename: Hidemasa
authors.initials: H
authors.lastname: Bono
authors.forename: Shugo
authors.initials: S
authors.lastname: Nakamura
authors.forename: Yoshihide
authors.initials: Y
authors.lastname: Hayashizaki
authors.forename: Yasushi
authors.initials: Y
authors.lastname: Okazaki
authors.forename: Katsutoshi
authors.initials: K
authors.lastname: Takahashi
mesh_terms: D000465:Algorithms; D000818:Animals; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D015723:Gene Library; D008297:Male; D020411:Oligonucleotide Array Sequence Analysis