Tami Gjorgjieva

@tamigj.bsky.social

Complex trait genetics, ethics and society, global research capacity building 🧬 🌍 ⚖️ PhD candidate with the Pritchard Lab @Stanford

Today is the last day to apply‼️ Thank you everyone for the incredible interest so far! We are especially looking for more folks with experience or willingness to learn and support trainees in metagenomics, microbiome, and/or bacterial/viral genetics 🧬. Spread the word!

Tami Gjorgjieva@tamigj.bsky.social · 3mo ago

Hi Genetics/Comp-Bio community 👋 Interested in mentoring a comp-bio research student in East Africa over the summer? Do you have any experience in bioinformatics, biostats, genome/RNA-seq analyses, ML, or metagenomics? We'd love to have you as a mentor in our new program! 🧵 (1/n)

Hi Genetics/Comp-Bio community 👋 Interested in mentoring a comp-bio research student in East Africa over the summer? Do you have any experience in bioinformatics, biostats, genome/RNA-seq analyses, ML, or metagenomics? We'd love to have you as a mentor in our new program! 🧵 (1/n)

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Why do schizophrenia GWAS signals look so flat across the genome? In our recent preprint, we explored why psychiatric disorders — and, more broadly, brain-related traits involving the central nervous system — appear to have unusual genetic architectures. 🧵1/n

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Staff scientist position (computational): I am looking for a computational scientist to join my genomics lab at Stanford. They should have an outstanding skillset in ML/statistical methods for genomic applications, postdoc experience and a strong publication record. #sciencejobs

What a joy to work on exciting science AND do it with a great friend like @itskatelawrence.bsky.social! Check out her 🧵 on our recent preprint with @sbmontgom.bsky.social:

Kate (Kathryn) Lawrence@itskatelawrence.bsky.social · last yr.

Excited to share my first PhD paper in the @sbmontgom.bsky.social lab with @tamigj.bsky.social (www.biorxiv.org/content/10.1...)! Standard QTL methods treat each gene independently. But what if a single variant regulates multiple nearby genes at once - what we call “allelic proxitropy”? 🧵 ⬇️

Standard methods are equivalent to a flashlight, looking at each gene independently. We combine signals from multiple genes, turning a floodlight onto the genome.

Modern GWAS can identify 1000s of significant hits but it can be hard to turn this into biological insight. What key cellular functions link genetic variation to disease? I'm very excited to present our new work combining associations and Perturb-seq to build interpretable causal graphs! A 🧵

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What do GWAS and rare variant burden tests discover, and why? Do these studies find the most IMPORTANT genes? If not, how DO they rank genes? Here we present a surprising result: these studies actually test for SPECIFICITY! A 🧵on what this means... (🧪🧬) www.biorxiv.org/content/10.1...

Specificity, length, and luck: How genes are prioritized by rare and common variant association studies

Standard genome-wide association studies (GWAS) and rare variant burden tests are essential tools for identifying trait-relevant genes. Although these methods are conceptually similar, we show by anal...

biorxiv.org

In a new preprint led by @TheNikhilMilind, we explored a fascinating paradox: For many traits the number of duplications or loss-of-function (LoF) mutations is correlated with phenotype. Curiously, for most traits, the AVERAGE direction of LoFs and Dups is the SAME. Why?

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🧬 What are protein language models (PLMs) actually learning about biology? Our paper introduces InterPLM - a framework that reveals interpretable features in PLMs using sparse autoencoders, giving us a window into how these models represent protein structure and function. 🧵(1/8)

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I’ve decided to leave Scientific American after an exciting 4.5 years as editor in chief. I’m going to take some time to think about what comes next (and go birdwatching), but for now I’d like to share a very small sample of the work I’ve been so proud to support (thread)