A bayesian approach to transcript estimation from gene array data: the BEAM technique

We present a new statistically optimal approach to estimate transcript levels and ratios from one or more gene array experiments. The Bayesian Estimation of Array Measurements (BEAM) technique uses a model of measurement noise and prior information to estimate biological expression levels. It provides a principled method to deal with negative expression level measurements, combine multiple measurements, and identify changes in expression level. BEAM is more flexible than existing techniques, because it does not assume a specific functional form for noise and prior models. Rather, it uses a more accurate noise model developed from experimental data, a process we illustrate here using Affymetrix yeast chips. Categories and Subject Descriptors J.3 [Computer Applications]: Life And Medical Sciences-biology and genetics; I.6.4 [Computing Methodologies]: Simulation and Modeling--model validation and analysis, model development General Terms measurement, verification Keywords DNA Microarrays...

• Type: Conference
• Year: 2002
• Where: RECOMB
• Authors: Ron O. Dror, Jonathan G. Murnick, Nicola A. Rinaldi, Voichita D. Marinescu, Ryan M. Rifkin, Richard A. Young
• Keywords: Computational Biology, Development General Terms, RECOMB 2002, Specific Functional Form, Verification Keywords Dna