Related Experiment Videos
Predicting transcription factor activities from combined analysis of microarray and ChIP data: a partial least
Anne-Laure Boulesteix1, Korbinian Strimmer
1Department of Statistics, University of Munich, Ludwigstr. 33, D-80539 Munich, Germany. anne-laure.boulesteix@stat.uni-muenchen.de
Theoretical Biology & Medical Modelling
|June 28, 2005
Summary
This study introduces a statistical method using partial least squares regression to accurately measure transcription factor activities (TFAs) from gene expression and DNA binding data. The approach enhances understanding of cellular regulatory networks and identifies functional interactions.
Area of Science:
- Molecular Biology
- Systems Biology
- Bioinformatics
Background:
- Understanding cellular regulatory mechanisms requires studying transcription factor (TF) networks.
- Standard microarray experiments cannot directly measure transcription factor activities (TFAs) due to post-translational modifications.
Purpose of the Study:
- To develop a statistical method for inferring true TFAs from combined mRNA expression and DNA-protein binding data.
- To address limitations of existing methods for TFA estimation.
Main Methods:
- Utilizing partial least squares (PLS) regression for TFA inference.
- Applying the method to analyze small sample sizes and detect functional TF interactions.
- Integrating mRNA expression and ChIP data for comprehensive analysis.
Main Results:
- The proposed PLS-based method accurately infers TFAs.
- Functional interactions among TFs can be detected through "meta"-transcription factors.
- The method identifies false positives in ChIP data and distinguishes between activation and suppression activities.
Conclusions:
- The method demonstrates strong performance on simulated and real biological data (yeast, E. coli).
- It overcomes limitations of prior TFA estimation approaches.
- Estimated TFAs can be used for further analyses like periodicity and differential regulation studies.
- An R package, "plsgenomics", is available for implementing the methods.