| The goal of the project is to develop a series of linked algorithms and software programs for high-performance computing in genetic analysis of complex human traits. This software should make semi-automatic discovery of genes involved in complex diseases possible. The algorithms must take into account evidence coming from different levels of genetic analysis (linkage, association studies, knowledge of the sequence of the human genome, literature data about disease). We will focus on exploiting highly parallelizable computation techniques in genetic analysis, building upon our previous joint research. The software will specifically target the analysis of large pedigrees spanning 5 or more generations, as can be found in human isolated populations and life stock. A parallel computer system (cluster) will be constructed to support software testing and high-performance computing. The algorithms and software will be tested and validated using data simulated under various genetic models. Also, commercial software and software available in the public domain (if available) will be used as a golden standard for comparison. Finally, the data will be applied to the numerous data sets that have been obtained in ongoing research projects of Erasmus and IC&G. |
