Mega2, the Manipulation environment or Genetic Analysis, is a unique open-source 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 and evolving collection of commonly-used genetic analysis programs. It has served an important role in the genetics research community worldwide. Under this proposal, we plan to enhance the capabilities of Mega2, 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 improve Mega2's large-scale data handling in order to meet the needs of the research community by extending Mega2 to interface with PLINK/SEQ, a rich and flexible open source system for handling large-scale whole- genome studies. We plan to make Mega2 much easier to extend, repair, and maintain by creating C++ objects to facilitate the addition of new input and output formats. We plan to extend Mega2's interoperability and usability by supporting more input formats and analysis programs (as prioritized by our users), restructuring Mega2 to process slices of data, and enabling Mega2 to generate scripts for running analysis programs and itself in parallel. We plan to continue to maintain Mega2 as a public resource, constantly revising it to support the very latest versions of the supported analysis programs, carrying out rigorous and extensive quality-control testing, maintaining and improving the documentation, and promoting Mega2. Accomplishment of these aims will significantly improve Mega2's reach, usability, data input handling capabilities, abilities to set up target analyses, extensibility, maintainability, and interoperability, thus ensuring continuing usefulness and availability of this widely-used software.

Public Health Relevance

Mega2 is a versatile program for reformatting data from a genetic study so that it can be easily analyzed by a large set of target analysis programs. 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.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Biodata Management and Analysis Study Section (BDMA)
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Krasnewich, Donna M
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University of Pittsburgh
Schools of Public Health
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Bui, Diem K; Jiang, Yingda; Wei, Xin et al. (2015) Genetic ME-a visualization application for merging and editing pedigrees for genetic studies. BMC Res Notes 8:241
Baron, Robert V; Conley, Yvette P; Gorin, Michael B et al. (2015) dbVOR: a database system for importing pedigree, phenotype and genotype data and exporting selected subsets. BMC Bioinformatics 16:91
Baron, Robert V; Kollar, Charles; Mukhopadhyay, Nandita et al. (2014) Mega2: validated data-reformatting for linkage and association analyses. Source Code Biol Med 9:26
Weeks, Daniel E; Tang, Xinyu; Kwon, Amy M (2009) Casares' map function: no need for a 'corrected' Haldane's map function. Genetica 135:305-7
Bhattacharjee, Samsiddhi; Kuo, Chia-Ling; Mukhopadhyay, Nandita et al. (2008) Robust score statistics for QTL linkage analysis. Am J Hum Genet 82:567-82
O'Brien, Frances G; Lim, Tien Tze; Winnett, David C et al. (2005) Survey of methicillin-resistant Staphylococcus aureus strains from two hospitals in El Paso, Texas. J Clin Microbiol 43:2969-72
Davis, A O; O'Leary, J O; Muthaiyan, A et al. (2005) Characterization of Staphylococcus aureus mutants expressing reduced susceptibility to common house-cleaners. J Appl Microbiol 98:364-72
O'Leary, Jessica O; Langevin, Mark J; Price, Christopher T D et al. (2004) Effects of sarA inactivation on the intrinsic multidrug resistance mechanism of Staphylococcus aureus. FEMS Microbiol Lett 237:297-302