Significance analysis of microarray transcript levels in time series experiments.

ABSTRACT:

Background

Microarray time series studies are essential to understand the dynamics of molecular events. In order to limit the analysis to those genes that change expression over time, a first necessary step is to select differentially expressed transcripts. A variety of methods have been proposed to this purpose; however, these methods are seldom applicable in practice since they require a large number of replicates, often available only for a limited number of samples. In this data-poor context, we evaluate the performance of three selection methods, using synthetic data, over a range of experimental conditions. Application to real data is also discussed.

Results

Three methods are considered, to assess differentially expressed genes in data-poor conditions. Method 1 uses a

SUBMITTER: Di Camillo B 

PROVIDER: S-EPMC1885839 | biostudies-literature | 2007 Mar

REPOSITORIES: biostudies-literature