Bayesian detection of non-sinusoidal periodic patterns in circadian expression data.

ABSTRACT:

Motivation

Cyclical biological processes such as cell division and circadian regulation produce coordinated periodic expression of thousands of genes. Identification of such genes and their expression patterns is a crucial step in discovering underlying regulatory mechanisms. Existing computational methods are biased toward discovering genes that follow sine-wave patterns.

Results

We present an analysis of variance (ANOVA) periodicity detector and its Bayesian extension that can be used to discover periodic transcripts of arbitrary shapes from replicated gene expression profiles. The models are applicable when the profiles are collected at comparable time points for at least two cycles. We provide an empirical Bayes procedure for estimating parameters of the prior distributi

SUBMITTER: Chudova D 

PROVIDER: S-EPMC3167694 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature