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.
| 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 |
| 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'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 |
| 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 |
