Recent biomedical research has made great progress in unveiling the complexity of human disease, while technological breakthroughs now allow much more detailed analysis of molecular behavior. As a result however, experimental results are frequently too complex for synthesis in the traditional model of tracing disease through individual genes. Instead, molecular pathways are gaining prominence as a new framework for analytic research. Pathways integrate information from across the entire genome while mirroring real biological processes. Disruption of the benign behavior of a pathway as a whole, not necessarily a single component of the pathway, could be the basis for disease. As yet, there exists no robust or straightforward means to transform the large-scale molecular expression data common to most genetic studies into meaningful data at the pathway level. To facilitate this promising mode of investigation, the PathOlogist has been developed as a resource capable of systematic and efficient pathway-centric analysis of molecular data. The PathOlogist is a new tool designed to automatically analyze large sets of genetic data within the context of molecular pathways. The tool aims to facilitate both a quantitative and qualitative analysis of pathway behavior in a format accessible to both laboratory researchers and informatics analysts. Foremost, the PathOlogist uses RNA expression data to calculate 2 descriptive metrics - activity and consistency - for each pathway in a set of more than 500 canonical pathways (source: Pathway Interaction Database http://pid.nci.nih.gov). Activity scores provide a measure of how likely the interactions within the pathway are to occur while consistency scores provide a measure of pathway logic by comparing the expected with de facto outcome of interactions. Pathway scores can be generated for any number of samples, and for any subset of the entire pathway collection. The program then allows a detailed exploration of the results through integrated visualization of pathway components, structure, and scores, hierarchical clustering of pathways and samples, and statistical analyses designed to identify associations between pathway scores and clinical features such as cancer type or patient survival. The PathOlogist provides a powerful means of identifying common molecular processes implicated in disease. By viewing molecular behavior at the pathway level, the metrics generated by the PathOlogist often provide further insight into disease pathology than could be gained from individual gene-based analyses. The tool is already being used for such diverse applications as predicting response to cancer treatment and identifying molecular signatures associated with cancer phenotype.
| Efroni, Sol; Carmel, Liran; Schaefer, Carl G et al. (2008) Superposition of transcriptional behaviors determines gene state. PLoS ONE 3:e2901 |
