Level: Intermediate
Thomas Walk, Large Plant Breeding Pipeline DB Manger, North Dakota State University
Ana Heilman Morales, Large Plant Breeding Pipeline DB Manger, North Dakota State University
Richard Horsley, Department Head, Professor, North Dakota State University
JMP provides a host of tools that are useful, not only for stand-alone analysis, but also integratation into existing data management and analysis systems. Over the years, specialized data management and analysis tools have been developed for crop breeders managing numerous experiments involving thousands of experimental breeding lines grown at multiple locations over many years. Here, we report on a set of JMP add-ins that have been developed to query a plant breeding MS SQL Server database, and to then analyze the raw data in mixed models built in JMP or ASReml, a specialized package for breeding research. In these add-ins, each DB query is made through a New SQL Query, with user interface boxes provided to select relevant search parameters.Results can be run through mixed model analysis directly in JMP or subjected to more specialized analysis in ASReml, which, in this case, is launched from JMP through RunProgram. Throughout the process, tables are split or otherwise managed to expedite analysis and to prepare for DB updates. Output from ASReml is read into JMP tables through Parse XML. Add-in components are separated into JSL functions for modular functionality in an object-oriented design. Overall, due to the range of available methods, the capability of standardizing tasks in JSL and add-ins, and the ease of creating user interfaces, JMP has become a central piece in plant breeding research at NDSU. We hope that the functionality demonstrated in this presentation will help others figure out how JMP might best be used in their situations.