We recently posted a medRxiv preprint on our large-scale data aggregation efforts for rare copy-number variants (rCNVs) across human diseases and disorders.
It's hard to believe, but this study actually started over five years ago as a final project in MIT's Quantitatve Genomics course co-taught by Profs. Leonid Mirny and Shamil Sunyaev during my first semester as a PhD student back in the fall...
Last week, we released the initial structural variant (SV) callset for the Genome Aggregation Database (gnomAD), which included nearly a half-million distinct SVs discovered across ~15 thousand human whole-genome sequences.
Recently, I wrote a short peice for a great local science news & media outlet, Science In The News (SITN), to explain how population-scale genetic sequencing is driving major advances in precision medicine.
The article is targeted primarily for the lay public (i.e. non-specialists), so it's mostly jargon-free. It gets even better for those among us who are more visually inclined learners: a fellow PhD student at HMS, Brad Wierbowski, put together some great graphical figures to explain the core concepts (thanks Brad!).
Our collaboration with Sam Schilit, Cynthia Morton, and the rest of the DGAP team on a case of congenital hearing loss with a de novo balanced translocation, dubbed DGAP242, was published this week in European Journal of Human Genetics. The article can be viewed here. Congrats to...
DevoEvoMedNew and improved version of our @biorxivpreprint, in which we justify classifying genes as not/expressed based on transcript abundance estimates. tl;dr genes with < 1-2 transcripts per million are not expressed. Short 🧵summarizes why...
kristenbrennandJoin us @YalePsych and @YaleGenetics!
We are hiring multiple postdocs! The scope of currently funded projects is broad, and scientists from any discipline with training or interest in stem cell models and neurogenomics are welcome to apply.
LauraLauraDatIt's day 3 of #INSAR2021! (Man, I still want to type INSAR2020) My latest: Using data from more than 750k people, @RyanLCollins13 and colleagues created scores for 17k genes that could help docs, families, etc., interpret genetic results about autism t.co/a8gTs3dN9f