Genomic Selection and Genome-wide Association Studies
Genomic selection using genome-wide SNP markers has rapidly become an accepted technology for genetic improvement in plant and animal species. However, current methodology for genomic prediction and selection focused on additive effects. For the 2014 allocation period, this group has focused on methodology development. They have successfully developed distributed memory and shared memory parallel computing tool that achieved nearly ideal scalability. With these new powerful tools and new methodology of genetic analysis, heavy data analysis work and large sample runs are expected during 2015. The group has requested the Framingham Heart Study data with 200 Gb of raw data. For 2015, the group's main usage of Itasca will be to improve the capability and test the limits of new MPI parallel computing tools and to analyze large datasets using their computing tools.
A bibliography of this group’s publications is attached.
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