Inference and Evaluation of the Functional Linkages Between Biologically Meaningful Gene Sets: A Gene Set Linkage Analysis Tool

At the molecular level, biological processes are defined as sets of genes. Identifying the functional linkages between well-established biological processes can create a conceptual network that reflects the framework of our knowledge about the mechanisms underlying life, at the biological process level. Molecular phenotypes observed in profiling experiments are also sets of "significant genes". Identifying the functional linkages between phenotypic gene sets and well-established biological processes may help to draw a connection with the molecular phenotype to our knowledge framework, providing insights into the nature, cause and functional implication of the molecular phenotype. Here, we develop the idea of functional association network and create a couple of tools, the predicted Arabidopsis interactome resource (PAIR) and the gene set linkage analysis (GSLA) tool, for the analysis of functional linkages between biologically meaningful gene sets. Through a series of systematic assessments and case studies, the utility of GSLA was illustrated. In contrast to the widely used annotation term enrichment analysis, which essentially detects the "identity" of a molecular phenotype and "annotates" it with established biological concepts, GSLA can provide additional functional insights into the potential origin and impact of the molecular phenotype, thereby help to interpret the significance of a novel undefined molecular phenotype using established biological concepts. This strength of GSLA is expected to complement the ability of currently available tools to meet the ever-increasing demand of profiling data analysis. The GSLA tool and its supporting PAIR database are freely accessible at http://www.cls.zju.edu.cn/pair/.