🧬 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...

Systematic common and rare variant association testing in 392,030 whole genomes in All of Us

Large-scale genome-wide association studies (GWAS) and rare variant association studies (RVAS) from population biobanks provide valuable resources for gene discovery in complex human traits. We presen...

medrxiv.org

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...

Integrating 730,947 exome sequences with clinical literature improves gene discovery

Accurate estimates of allele frequencies aid in genetic discovery, including rare disease diagnosis, common disease investigations, and population genetics. Here, we present the Genome Aggregation Dat...

medrxiv.org

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...

Pan-UK Biobank genome-wide association analyses enhance discovery and resolution of ancestry-enriched effects - Nature Genetics

Genome-wide analyses for 7,266 traits leveraging data from several genetic ancestry groups in UK Biobank identify new associations and enhance resources for interpreting risk variants across diverse p...

nature.com

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...

Variant scoring performance across selection regimes depends on variant-to-gene and gene-to-disease components

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution

biorxiv.org

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...

The Scalable Variant Call Representation: Enabling Genetic Analysis Beyond One Million Genomes

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution

biorxiv.org

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...

A genomic mutational constraint map using variation in 76,156 human genomes - Nature

A genomic constraint map for the human genome constructed using data from 76,156 human genomes from the Genome Aggregation Database shows that non-coding constrained regions are enriched for regulator...

idp.nature.com

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~