Presentation Number: 4

Sivachenko, Andrey - Ariadne Genomics, Inc.

Author(s): A. Y. Sivachenko, A. Yuryev, N. Daraselia, I. Mazo

Title: Integration of Expression Data and Transcriptional Control Network: Significant Regulators Driving Expression Changes

Abstract: Microarrays provide an invaluable insight into the biomolecular mechanisms, however raw results are disjoint genome-wide “one-gene-at a time” datasets with high levels of noise. Placing data into the biological context through integration with different data sources is critical both for noise reduction and for objectively quantifiable system-level hypothesis formulation. We analyze differential expression (DE) data in the context of large network of known transcription regulation events. DE data sample downstream of a regulator is compared to the sampling distribution derived from the network, with network connectivity taken into account. The analysis is aimed at elucidating regulators with statistically significant patterns of downstream expression changes and explaining DE data in terms of activated/suppressed regulatory cascades. The set of plausible regulatory events provides conceptual data reduction and a step towards elucidating/building extended pathways. We apply our analysis to a few disease datasets, demonstrate robustness and statistical significance of the results, and show that the sets of regulators suggested as putatively involved in the differential response are potentially interesting biologically and exhibit statistically significant overlap with sets of known disease associated genes. Assembling significant regulators into a putative signaling pathway and applications of our procedure to other networks (metabolic, binding) are also discussed.