To compare the performance of selected rare-variant association methods for fine-mapping a disease locus. In our investigation, we focus on the localization of association signal to between \(950kbp - 1050kbp\) within a 2Mb candidate genomic region.
We use variant data simulated from coalescent trees. Our work on localization of association signal extends that of Burkett et al., which investigated the ability to detect association signal in the candidate region, without regard to localization.
To illustrate ideas, we start by working through a particular example dataset as a case study for insight into several popular methods.
Next, we perform a simulation study involving 200 sequencing datasets and score which association method localizes best, overall.