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The PathOlogist: an automated tool for pathway-centric analysis

Sharon I Greenblum13*, Sol Efroni2, Carl F Schaefer3 and Ken H Buetow3

Author Affiliations

1 Department of Genome Sciences, University of Washington, Seattle WA, USA

2 Bar-Ilan University, Ramat Gan, Israel

3 Laboratory of Population Genetics, National Cancer Institute, National Institutes of Health, Rockville MD, USA

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BMC Bioinformatics 2011, 12:133  doi:10.1186/1471-2105-12-133

Published: 4 May 2011

Abstract

Background

The PathOlogist is a new tool designed to transform large sets of gene expression data into quantitative descriptors of pathway-level behavior. The tool aims to provide a robust alternative to the search for single-gene-to-phenotype associations by accounting for the complexity of molecular interactions.

Results

Molecular abundance data is used to calculate two metrics - 'activity' and 'consistency' - for each pathway in a set of more than 500 canonical molecular pathways (source: Pathway Interaction Database, http://pid.nci.nih.gov webcite). The tool then allows a detailed exploration of these metrics through integrated visualization of pathway components and structure, hierarchical clustering of pathways and samples, and statistical analyses designed to detect associations between pathway behavior and clinical features.

Conclusions

The PathOlogist provides a straightforward means to identify the functional processes, rather than individual molecules, that are altered in disease. The statistical power and biologic significance of this approach are made easily accessible to laboratory researchers and informatics analysts alike. Here we show as an example, how the PathOlogist can be used to establish pathway signatures that robustly differentiate breast cancer cell lines based on response to treatment.