Systematic management and analysis of yeast gene expression data

Abstract

We report steps toward the systematic management, standardization, and analysis of functional genomics data. We developed the ExpressDB database for yeast RNA expression data and loaded it with ~17.5 million pieces of data reported by 11 studies with three different kinds of high-throughput RNA assays. A web-based tool supports queries across the data from these studies. We examined comparability of data by converting data from 9 studies (217 conditions) into mRNA relative abundance estimates (ERAs) and by clustering of conditions by ERAs. We report on generation of ERAs and condition clustering for non-microarray data (5 studies, 63 conditions) and describe initial attempts to generate microarray-based ERAs (4 studies, 154 conditions), which exhibit increased error, on our web site http://arep.med.harvard.edu/ExpressDB. We recommend standards for data reporting, suggest research into improving comparability of microarray data through quantifying and standardizing control condition RNA populations, and also suggest research into the calibration of different RNA assays. We introduce a model for a database that integrates different kinds of functional genomics data, Biomolecule Interaction, Growth and Expression Database (BIGED).