I'm a graduate research student pursuing a PhD in Human Genetics at the University of Utah. My current work is in identifying, curating, and understanding genomic structural variants (SVs).
I earned my Bachelor's of Science Degree in Bioinformatics with a minor in Computer Science from Brigham Young University in 2016.
De novo structural variants in ASD
There is a known enrichment of SVs in Autism Spectrum Disorders (ASD). I analyzed the rates and patterns of spontaneous SVs in a very large ASD family cohort (preprint on BioRxiv) to learn more about how often these variants occur, what effects they have in ASD risk, the impact of parental age on SV risk, and the molecular mechanisms responsible. My work was featured in a Spectrum News article after I presented a poster at ASHG 2020.
Visually reviewing the sequencing evidence for SVs is very important, because lots of false positives variant calls occur. Samplot (preprint on BioRxiv) facilitates making plots, filtering, and even curating via a deep learning classifier.
I developed a tool (published in GigaScience) for creating image views of genomic intervals, automatically storing them in the cloud, deploying a website to view/score them, and retrieving scores for analysis, with support for sequencing data from BAM or CRAM files from Illumina, or long-read technologies (ONT/PacBio).
In a project for a BYU CS Capstone in Big Data, my team (Artem Golotin, Darian Ramage, and I) developed a scalable system for monitoring streaming seismic signals in a developing aftershock sequence. This could be used to study earthquakes in more detail (as well as to identify illicit nuclear testing). Presented at LLNL and BYU.
Computational tool development/distribution
I'm a huge fan of the outdoors and spend as much time as I can hiking, canyoneering, or skiing. Check out my Instagram for more: