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Jingyou Rao @jingyour.bsky.social · 2d

VESS is happening tomorrow (Oct 7). See you there!
First speaker: Shelby Hemker (Dr. Jacob Kitzman Lab, University of Michigan)
Second speaker: Karl Romanowicz (Dr. Calin Plesa Lab, University of Oregon) @kroman.bsky.social
Link: www.varianteffect.org/seminar-seri...

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Reposted by Jingyou Rao

The Wells Lab of UCLA @wellslab.bsky.social · 8d

The first (of hopefully many) reports to come from our collaboration with @hjp.bsky.social

We present a new type of cell fitness assay that allows you to both quantify and explain differences across human donors in cell proliferation and sensitivity to environmental toxicants.

bioRxiv Genetics @biorxiv-genetic.bsky.social · 9d

Cell villages and Dirichlet modeling map human cell fitness genetics https://www.biorxiv.org/content/10.1101/2025.09.26.678880v1

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Reposted by Jingyou Rao

Harold Pimentel @hjp.bsky.social · 16d

Super excited to have this out. Thanks very much to the reviewers who helped improve this manuscript. Congrats to @jingyour.bsky.social!

bsky.app/profile/bioi...

Bioinformatics Advances @bioinfoadv.bsky.social · 16d

🧩 Recently published in Bioinformatics Advances: “Rosace-AA: Enhancing interpretation of deep mutational scanning data with amino acid substitution and position-specific insights”

Full article available: https://doi.org/10.1093/bioadv/vbaf218

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Reposted by Jingyou Rao

Yun S. Song @yun-s-song.bsky.social · 16d

We are excited to share GPN-Star, a cost-effective, biologically grounded genomic language modeling framework that achieves state-of-the-art performance across a wide range of variant effect prediction tasks relevant to human genetics.
www.biorxiv.org/content/10.1...
(1/n)

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Reposted by Jingyou Rao

Sasha Gusev @sashagusevposts.bsky.social · Aug 10

I wrote about how genetic risk works in the context of embryo selection and how people often think about it all wrong. A short 🧵:

What we talk about when we talk about risk

How embryo selection exploits our flawed intuitions about risk

open.substack.com

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Reposted by Jingyou Rao

Anshul Kundaje @anshulkundaje.bsky.social · Aug 19

@jengreitz.bsky.social l & my lab want to co-hire a computational biologist/biostatistician with project management expertise to help map the regulatory code of the human genome and discover genetic mechanisms of disease.

Details below
careersearch.stanford.edu/jobs/computa...

Plz RT

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Reposted by Jingyou Rao

Atlas of Variant Effects Alliance @varianteffect.bsky.social · Aug 19

Why yes! You can watch previous Variant Effects Seminar Series talks on our YouTube channel!
ℹ️ www.varianteffect.org/previous-sem... 📺 www.youtube.com/playlist?lis...

#Genomics #Seminar #EarlyCareerResearchers #ScientificSeminar #PrecisionMedicine

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Reposted by Jingyou Rao

Harold Pimentel @hjp.bsky.social · Aug 15

Very excited to have this out! Here, we take inspiration from model selection MR to decouple direct and indirect effects in DMS experiments. Check out Jingyou's explainer and paper below:

bsky.app/profile/jing...

Jingyou Rao @jingyour.bsky.social · Aug 4

How do we decouple the effects of two functional phenotypes in protein deep mutational scanning (DMS)?
Meet Cosmos, our new statistical framework for causal inference in multi-phenotype DMS.
www.biorxiv.org/content/10.1...
[1/n]

Cosmos: A Position-Resolution Causal Model for Direct and Indirect Effects in Protein Functions

Multi-phenotype deep mutational scanning (DMS) experiments provide a powerful means to dissect how protein variants affect different layers of molecular function, such as abundance, surface expression...

www.biorxiv.org

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Reposted by Jingyou Rao

Roshni Patel @roshnipatel.bsky.social · Aug 6

Bittersweet to be leaving @docedge.bsky.social after a wonderful postdoc, but excited to share that I'm joining @uoregon.bsky.social next month as an Assistant Professor in the Department of Data Science.

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Jingyou Rao @jingyour.bsky.social · Aug 4

Try Cosmos in Python now!
See vignettes to get started
🔗 Code: github.com/pimentellab/...

GitHub - pimentellab/cosmos: A Position-Resolution Causal Model for Direct and Indirect Effects in Protein Functions

A Position-Resolution Causal Model for Direct and Indirect Effects in Protein Functions - pimentellab/cosmos

github.com

Jingyou Rao @jingyour.bsky.social · Aug 4

We applied Cosmos to 3 DMS datasets:
Kir2.1: abundance → surface expression
PDZ3: abundance → CRIPT binding
KRAS: abundance → RAF1_RBD binding
Cosmos clearly separates direct binding residues from those with indirect effects.
[6/n]

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Jingyou Rao @jingyour.bsky.social · Aug 4

How does it work?
Cosmos aggregates mutation effects by position, learns interpretable causal graphs via Bayesian model selection, and outputs residue-level direct vs indirect effects.
[5/n]

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Jingyou Rao @jingyour.bsky.social · Aug 4

Cosmos answers three key questions:
1️⃣ Is there a causal link between the phenotypes?
2️⃣ How strong is it?
3️⃣ What would the downstream phenotype look like if we “normalized” the upstream one (i.e., counterfactual inference)?
[4/n]

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Jingyou Rao @jingyour.bsky.social · Aug 4

Cosmos is a Bayesian framework that performs residue-level causal inference to decouple how mutations influence upstream vs downstream functions.
No need for detailed biophysical models—just stats and data.
[3/n]

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Jingyou Rao @jingyour.bsky.social · Aug 4

Multi-phenotype DMS experiments are revealing how mutations impact different protein functions.
But these phenotypes are often causally linked—e.g., when measuring activity, we may also capture effects propagated from abundance.
So how do we tell what’s direct vs indirect?
[2/n]

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Jingyou Rao @jingyour.bsky.social · Aug 4

How do we decouple the effects of two functional phenotypes in protein deep mutational scanning (DMS)?
Meet Cosmos, our new statistical framework for causal inference in multi-phenotype DMS.
www.biorxiv.org/content/10.1...
[1/n]

Cosmos: A Position-Resolution Causal Model for Direct and Indirect Effects in Protein Functions

Multi-phenotype deep mutational scanning (DMS) experiments provide a powerful means to dissect how protein variants affect different layers of molecular function, such as abundance, surface expression...

www.biorxiv.org

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Reposted by Jingyou Rao

Alicia Izquierdo @aliciaizquierdo.bsky.social · Aug 1

Suspension of all grants to UCLA www.latimes.com/california/s...

Trump freezes $200 million in UCLA science and medical research funding, citing antisemitism

The Trump administration has frozen roughly $200 million in National Science Foundation, National Institutes of Health and other federal agency-funded research at UCLA, citing allegations the school d...

www.latimes.com

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Reposted by Jingyou Rao

Yun S. Song @yun-s-song.bsky.social · Jun 6

The 2026 Probabilistic Modeling in Genomics (ProbGen) meeting will be held at UC Berkeley, March 25-28, 2026. We have an amazing list of keynote speakers and session chairs:
probgen2026.github.io

Please help spread the news.

Home - ProbGen 2026

Your Site Description

probgen2026.github.io

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Jingyou Rao @jingyour.bsky.social · Jul 31

Perfect first day: receiving a set of new pipettes! Can’t wait to do more cool experiments with the lab for the next few years. @willowcoyote.bsky.social

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Reposted by Jingyou Rao

Harold Pimentel @hjp.bsky.social · Jul 21

Super proud of my first student, @jingyour.bsky.social! Well done! Looking forward to the amazing work you will do in the future 🥲 bsky.app/profile/jing...

Jingyou Rao @jingyour.bsky.social · Jul 21

Thrilled to share that I just successfully defended my PhD! Thanks to my committee, collaborators, and everyone who’d supported me throughout my seven years at UCLA. A special thank you to my PI Harold for his incredible mentorship! @hjp.bsky.social

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Jingyou Rao @jingyour.bsky.social · Jul 21

Thrilled to share that I just successfully defended my PhD! Thanks to my committee, collaborators, and everyone who’d supported me throughout my seven years at UCLA. A special thank you to my PI Harold for his incredible mentorship! @hjp.bsky.social

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Reposted by Jingyou Rao

Doug Fowler @dougfowler.bsky.social · Jul 21

Interested in using functional data to understand clinical variants? Been hunting for a good review of the topic? We just wrote one! rdcu.be/exaEU

Multiplexed assays of variant effect for clinical variant interpretation

Nature Reviews Genetics - Multiplexed assays of variant effect (MAVEs) are highly scalable experimental approaches used to generate functional data for genetic variants. In this Review, McEwen et...

www.nature.com

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Reposted by Jingyou Rao

Harold Pimentel @hjp.bsky.social · Jul 2

Very excited to have this work out by @jeromics.bsky.social ! Please check it out.

I think my favorite story from the supplement is how impactful normalization can be in this context.

bsky.app/profile/jero...

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Reposted by Jingyou Rao

Jerome @jeromics.bsky.social · Jun 30

Check out our new preprint on Lilace, a statistical tool for scoring FACS-based deep mutational scanning experiments! Lilace directly models the shift between variant fluorescence distributions and provides score uncertainty estimates to better assess reliability and reproducibility. (1/3)

Accurate variant effect estimation in FACS-based deep mutational scanning data with Lilace

Deep mutational scanning (DMS) experiments interrogate the effect of genetic variants on protein function, often using fluorescence-activated cell sorting (FACS) to quantitatively measure molecular ph...

www.biorxiv.org

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Reposted by Jingyou Rao

bioRxiv Bioinfo @biorxiv-bioinfo.bsky.social · Jun 28

Accurate variant effect estimation in FACS-based deep mutational scanning data with Lilace https://www.biorxiv.org/content/10.1101/2025.06.24.661380v1

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