Mega 2: Manipulation Environment for Genetic Analyses

University Of Pittsburgh At Pittsburgh, Pittsburgh PA

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Linked publications & trials

Abstract

Mega2, the Manipulation Environment for Genetic Analysis, is a unique computer program for facilitating the creation of analysis-ready datasets from data gathered as part of a genetic study. Mega2 transparently allows users to process genetic data for family-based or case/control studies accurately and efficiently. In addition to data validation checks, Mega2 provides analysis setup capabilities for a broad choice of commonly-used genetic analysis programs. It has served an important role in the genetics research community worldwide. Under this proposal, we plan to make Mega2 a powerful open-source application with highly enhanced capabilities, while applying best practices in software engineering to meet these critical needs of an open-source project: portability across OS platforms, ability to evolve with the needs of genetics research, extensive documentation, maximizing code reuse, as well as systematic testing, debugging and maintenance. Specifically, we plan to significantly improve Mega2's usability, data input handling capabilities, its abilities to set up target analyses, and its graphical presentation and storage of data statistics, diagnostics, and results. We will also develop an Application Programming Interface and improved documentation and tutorials. Mega2 has been used to accelerate gene discovery studies for a large list of complex human diseases. Improving this crucial resource will have a significant impact on speeding up the gene-discovery process, which in turn will ease the healthcare burden due to complex genetic disease in the US and world-wide. Relevance: Mega2 is used in many different studies of the genetics of complex human diseases, enabling researchers to swiftly change file formats and prepare files for statistical analysis and transparently processing genetic data accurately and efficiently. As such, Mega2 has and will continue to markedly accelerate the mapping and identification of susceptibility loci for complex human diseases.