Identifying significant temporal variation in time course microarray data without replicates.

ABSTRACT:

Background

An important component of time course microarray studies is the identification of genes that demonstrate significant time-dependent variation in their expression levels. Until recently, available methods for performing such significance tests required replicates of individual time points. This paper describes a replicate-free method that was developed as part of a study of the estrous cycle in the rat mammary gland in which no replicate data was collected.

Results

A temporal test statistic is proposed that is based on the degree to which data are smoothed when fit by a spline function. An algorithm is presented that uses this test statistic together with a false discovery rate method to identify genes whose expression profiles exhibit significant temporal variatio

SUBMITTER: Billups SC 

PROVIDER: S-EPMC2682797 | biostudies-literature | 2009 Mar

REPOSITORIES: biostudies-literature