🧬 New preprint! We present an All by All analysis in All of Us: common and rare variant association testing across 392,030 whole genomes and 3,602 phenotypes. 1.337 trillion tests, ~50k significant signals, all publicly browseable. www.medrxiv.org/content/10.6...

Excited to share our new preprint on gnomAD v4! We present the full analysis of 730,947 exomes — new constraint metrics, improved LoF annotation (LOFTEE-2), LLM-based literature curation, and a unified framework for gene discovery and rare disease diagnosis. www.medrxiv.org/content/10.6...

A project many years in the process, we’re pleased to present our work on multi-ancestry meta-analysis across a boatload of traits in the UK Biobank: www.nature.com/articles/s41...

We’ve put up summary statistics for over 3,000 traits in the All of Us resource, and a shiny new browser alongside it! Explore your favorite gene or phenotype here: allbyall.researchallofus.org #ASHG24

We have a new preprint that we’d love feedback on! We benchmarked a bunch of variant scoring methods to figure out what they were actually doing, and how they performed across selection regimes: www.biorxiv.org/content/10.1...

Welcome new followers (and thanks @michelnivard.bsky.social)! I’m loving the critical mass, and to celebrate, I’ll post some exciting new content (my first time posting here and not on the the other site)

Recently out on #bioRxiv: our updated approach to identify regional variability in missense mutation intolerance (“constraint”) in protein-coding genes using the gnomAD database. www.biorxiv.org/content/10.1... 1/10

As genomic analyses scale to millions of exomes/genomes, we need a scalable infrastructure to process/QC/handle these data while retaining all the metrics needed for downstream analysis. A new preprint from the Hail team proposes a way to do this! Comments welcome: www.biorxiv.org/content/10.1...

Thrilled to have our work on gnomAD out in print at Nature today. With 76K genomes, we can look beyond the coding genome and into the non-coding genome to find regions important for human disease idp.nature.com/authorize?re...

Excited for my first post on this new site to share our work in print at AJHG using variant call data to estimate DNA contamination. As our sample sizes get into the millions of genomes, we need methods like this to efficiently process and quality control the data authors.elsevier.com/c/1i8PAgeX6LB~