Implications: Identification of causal variant patterns in complex disease GWAS data.
Unmet need: Current gold standard software is slow.
IP Status: Licenses to software are available.
Project status: Functional software is ready and in use.
Genome-Wide Association Studies (GWAS) have identified thousands of genomic regions associated with complex human traits and diseases. The real challenge is the fine-mapping of these regions to identify causal mutation patterns. Identification of causal mutations can lead to the discovery of new therapeutic targets and reveal disease mechanisms. We at the University of Helsinki developed a software package, FINEMAP, for ultrafast high-resolution fine-mapping of genomic regions. FINEMAP is scalable to large sample sizes and even to whole chromosome level. It achieves the accuracy of existing gold standard methods in a fraction of their processing time.
Finnish Institute for Molecular Medicine, University of Helsinki