Genome-wide association studies(GWAS) are used to find associations betweengenetic markers and diseases. One part of GWAS is to study interactions be-tween markers which can play an important role in the risk for the disease. Thesearch for interactions can be computationally intensive. The aim of this thesiswas to improve the performance of software used for gene-environment interac-tion by using parallel programming techniques on graphical processors. A studyof the new programs performance, speedup and efficiency was made using mul-tiple simulated datasets. The program shows significantly better performancecompared with the older program.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-163215 |
| Date | January 2015 |
| Creators | Berglund, Daniel |
| Publisher | KTH, High Performance Computing and Visualization (HPCViz) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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