Daniel Taliun

My research focuses on developing novel scalable computational algorithms and software tools for large-scale sequencing-based genetic association studies. My work scope includes methods and tools for integration and analysis of genetic and clinical data, secure web-based tools for interactive data analyses and visualizations, secure data sharing, and scalable data analysis workflows for cloud computing computational platforms. Together with many collaborators from the US, I have analyzed high-depth (average coverage of 38X) whole-genome sequencing (WGS) data from more than 53,000 individuals in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. My main contributions to this work included analysis of the distribution of putative loss-of-function variants in protein-coding genes, examining the distribution of singletons in regulatory elements, and comparing the deep whole genome and whole exome sequencing experiments, and evaluation of different genetic variant calling pipelines. I have developed and implemented the BRAVO variant browser (http://bravo.sph.umich.edu) for sharing and interactive visualization of more than 700 million genetic variants found in TOPMed WGS data.