Genetics
Genetics provides two methods in JMP to help you analyze your genetic data and use that data to simulate a breeding program to predict the optimum genetic crosses to make.
• The Marker Statistics platform provides a convenient method for exploring several properties of all the biallelic markers in a data set, for the purpose of quality control (QC) and possibly selecting markers to be removed from the analysis See “Marker Statistics”.
• The Marker Simulation platform simulates the progeny from a specified set of crosses using biallelic markers and predictor formulas generated using the Response Screening platform (See “Response Screening” in the Predictive and Specialized Modeling book.) saved in your data table. This process enables you to test various crosses to estimate which crosses will generate progeny with the desired combinations of traits. See “Marker Simulation”.
• This report is used to assess different measures of genetic relatedness between pairs of individuals based on their genetic markers. The output of the platform is a genomic relationship matrix with n rows by n columns (n = number individuals in the data table). The matrix can be used to fit GBLUP models under the Fit Model platform with the Response Screening personality. The relationship matrix can also be used to assess groups of related individuals via principal component analysis and clustering. See “Marker Relatedness”.