On the Choice and Number of Microarrays for Transcriptional Regulatory Network Inference

Background: Transcriptional regulatory network inference (TRNI) from large compendia of DNA microarrays has become a fundamental approach for discovering transcription factor (TF)-gene interactions at the genome-wide level. In correlation-based TRNI, network edges can in principle be evaluated using standard statistical tests. However, while such tests nominally assume independent microarray experiments, we expect dependency between the experiments in microarray compendia, due to both project-specific factors (e.g., microarray preparation, environmental effects) in the multi-project compendium setting and effective dependency induced by gene-gene correlations. Herein, we characterize the nature of dependency in an Escherichia coli microarray compendium and explore its consequences on the problem of determining which and how many arrays to use in correlation-based TRNI. Results: We present evidence of substantial effective dependency among microarrays in this compendium, and characteri...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Elissa J. Cosgrove, Timothy S. Gardner, Eric D. Kolaczyk
• Keywords: BMCBI 2010, Compendium, Correlation-based Trni, Effective Dependency