Title thesis: High-throughput open source computational methods for genetics and genomics
Biology is increasingly data driven by virtue of the development of high-throughput technologies, such as DNA and RNA sequencing. By creating software solutions together with molecular biologists new insights were gained in biological processes in nematodes and plants. These software solutions were published as free and source software in the public domain, so as to make it easier for others to analyse data which impacts the wider research community. The thesis contributed, for example, to multiple QTL mapping in R/qtl, a high-throughput computational method for predicting what sections of a genome correlate with, for example, gene expression. The thesis also presents tools for scaling up next generation sequencing (NGS) alignment processing through the use of multiple cores on a computer and discusses computational bottlenecks in large scale computing and the need for big biology software development for the biomedical sciences.