abeha.bsky.social
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abeha.bsky.social
@abeha.bsky.social
PhD candidate in Human Genetics @Vanderbilt University
Reposted by abeha.bsky.social
Excited to share our latest work on the factors that determine what genes we find (and don't find!) in GWAS and burden tests.

We describe a critical concept that we call *specificity*.

Led by Jeff Spence and Hakhamanesh Mostafavi:
How do GWAS and rare variant burden tests rank gene signals?

In new work @nature.com with @hakha.bsky.social, @jkpritch.bsky.social, and our wonderful coauthors we find that the key factors are what we call Specificity, Length, and Luck!

🧬🧪🧵

www.nature.com/articles/s41...
Specificity, length and luck drive gene rankings in association studies - Nature
Genetic association tests prioritize candidate genes based on different criteria.
www.nature.com
November 7, 2025 at 4:08 AM
Reposted by abeha.bsky.social
Excited for a major milestone in our efforts to map enhancers and interpret variants in the human genome:

The E2G Portal! e2g.stanford.edu

This collates our predictions of enhancer-gene regulatory interactions across >1,600 cell types and tissues.

Uses cases 👇

1/
September 18, 2025 at 4:14 PM
Reposted by abeha.bsky.social
The difference between doing a project and presenting it. An observation can lead to many avenues of explorations before focus turns to a specific discovery. Presenting it, in a talk / paper, follows inversely, with broad perspectives coming before & after the specific discovery.
August 18, 2025 at 3:43 AM
Reposted by abeha.bsky.social
@hggadvances.bsky.social latest study leverages single-cell transcriptomics to explore genetic regulation of gene expression in mid-brain neurons & develop genetic models of cell type and cell-state adjusted expression patterns.

Read more here: www.cell.com/hgg-advances... #ASHG
January 13, 2025 at 2:15 PM
Reposted by abeha.bsky.social
Specificity, length, and luck: How genes are prioritized by rare and common variant association studies https://www.biorxiv.org/content/10.1101/2024.12.12.628073v1
December 16, 2024 at 10:33 AM
Reposted by abeha.bsky.social
Million Veteran Program & FinnGen teams are pleased to release v1 meta-analysis of MVP, FinnGen and UKBB GWAS data. This first version includes ~300 binary disease definitions across >1.5 M individuals.
Browse scans at: mvp-ukbb.finngen.fi
December 5, 2024 at 12:53 PM