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Shubhankar Londhe

@slondhe.bsky.social
189 followers 397 following 10 posts

PhD student @gagneurlab.bsky.social (TU Munich and Helmholtz Munich). Interested in rare variant genetics. shubhankarlondhe.github.io

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Shubhankar Londhe @slondhe.bsky.social · 07/10/2026
Together with @evaholtkamp.bsky.social and @gagneurlab.bsky.social And a huge thanks to the entire team @gtsitsiridis.bsky.social, @anna-strvt.bsky.social, @pedrotomazdasilva.bsky.social, @johahi.bsky.social, and @hilaryfinucane.bsky.social.
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Shubhankar Londhe @slondhe.bsky.social · 07/10/2026
Code free and open source github.com/gagneurlab/u... Not a UK Biobank user? A subset of UKBBGym, reproducible from Genebass summary statistics, is available here: huggingface.co/datasets/gag...
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Shubhankar Londhe @slondhe.bsky.social · 07/10/2026
Good news for training pathogenicity models! Performance on UKBBGym strongly predicts ClinVar classification performance (ρ = 0.86), without favoring scores trained on clinical labels (and all accompanying human-label biases). > Clinical relevance without circularity
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Shubhankar Londhe @slondhe.bsky.social · 07/10/2026
We next ask whether wet-lab data from DMS better predict the phenotypes of human carriers than computational scores. The answer is sobering. In two of the four testable proteins, computational scores correlated significantly better with variant effects on phenotype than experimental readouts.
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Shubhankar Londhe @slondhe.bsky.social · 07/10/2026
For SNVs, scores that model transcriptional regulation show modest correlations with protein abundance but poor correlations with quantitative traits. Evolutionary evidence matters more for traits than for protein abundance. Missense, splicing, and LoF scores performed better across both readouts.
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Shubhankar Londhe @slondhe.bsky.social · 07/10/2026
For each score, we measure how well it ranks variants within an allelic series, e.g., how well AlphaMissense orders LDLR variants by the average (covariate-adjusted) LDL cholesterol of carriers of these variants. We did this for 670 established gene-trait pairs and protein abundance of 1,076 genes.
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Shubhankar Londhe @slondhe.bsky.social · 07/10/2026
Variant scores are central to human genetics, from diagnosis to target discovery. But how well do they capture variant effects in human carriers? We tested this with ultra-rare WGS variants, quantitative traits, and Olink plasma proteomics from the UK Biobank. 🧵 doi.org/10.64898/202...
doi.org
Phenotypes of ultra-rare variant carriers benchmark variant effect scores
Human genetics needs benchmarks for evaluating variant scores against observed phenotypic consequences. We therefore present UKBBGym, which evaluates coding and non-coding scores against plasma protein abundance and quantitative traits observed in carriers of ultra-rare variants in the UK Biobank. This design avoids ascertainment biases of clinical labels, potential physiological mismatch of experimental assays, and confounding pertaining to common-variant associations. UKBBGym recapitulates relative performance on pathogenicity prediction while enabling comparison across variant classes and molecular mechanisms. This shows that scores designed for coding and splicing variants correlate more strongly with protein abundance and quantitative traits than scores modelling transcriptional regulation. Moreover, experimental assays do not consistently outperform computational scores for predicting missense effects. Comparing captured to detectable variance indicates scope for improvement, particularly for indels and loss-of-function variants. Finally, for coding variants, UKBBGym can be reproduced from public summary statistics, providing an accessible population-phenotype benchmark complementary to clinical labels and experimental assays. ### Competing Interest Statement The authors have declared no competing interest. Helmholtz Association of German Research Centres, project DeepVar, ZT-I-PF-5-156 Deutsche Forschungsgemeinschaft, https://ror.org/018mejw64, 535971044, 461264291, 553375143 European Research Council, 101118521 European Molecular Biology Organization, Scientific Exchange Grant #12502 European Union, Horizon Europe research and innovation program under grant agreement N°101156595
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Pedro Beltrao @pedrobeltrao.bsky.social · 23/06/2026
Not being able to access the @ukbiobank.ac.uk is becoming a significant issue for a PhD student in our group and I can only imagine this is mirrored in many other places. It would be fantastic to at least have a timeline we could work with.
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Shubhankar Londhe @slondhe.bsky.social · 14/10/2025
Why be satisfied with coding variant gene impairments? Check out Eva’s poster to learn how we scale DeepRVAT to the WGS UKBiobank. It’s been great fun being a part of this project! #ASHG25
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Shubhankar Londhe @slondhe.bsky.social · 14/10/2025
Excited to share UKBBGym at #ASHG25, a new benchmark for variant effect predictors using WGS, proteomics and phenotypes from 500K UKBiobank participants. Stop by for insights on the impact of non-coding variants and how computational scores stack up against exp assays. Poster 5022W, Wed 2:30-4:30.
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Gagneur lab @gagneurlab.bsky.social · 09/09/2025
The Solvathons have been one of our most exciting research community experiences: Hands-on, effective – solving real cases during the events, and multidisciplinary – from clinicians to bioinformaticians. Thumbs up to the SolveRD community. Looking for more now with @erdera.bsky.social rdcu.be/eFaqO
rdcu.be
The Solve-RD Solvathons as a pan-European interdisciplinary collaboration to diagnose patients with rare disease
Nature Genetics - This Perspective presents the Solve-RD Solvathon model, an innovative, pan-European framework uniting clinical and bioinformatics experts to diagnose rare diseases through...
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Reposted by Shubhankar Londhe
Samarendra Pani @samarendra-pani.bsky.social · 24/07/2025
[1/8] *New Open-Access Long Read Resource*. We sequenced 1,019 genomes from the 1000 Genomes Project sample cohort using @nanoporetech.com long-read sequencing (LRS) to median 17x coverage. Publication at go.nature.com/4ffPb8f. @hhu.de @crg.eu @embl.org @impvienna.bsky.social
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Gagneur lab @gagneurlab.bsky.social · 23/07/2025
Today at 12:20 in the HIT-Seq COSI, @lauradmartens.bsky.social Laura Martens will present her results on spatial chromatin accessibility data deconvolution #ISMBECCB2025. Great collab with Sarah Ouologuem and @fabiantheis.bsky.social Proceedings paper: doi.org/10.1093/bioi...
doi.org
Spatial transcriptomics deconvolution methods generalize well to spatial chromatin accessibility data
AbstractMotivation. Spatially resolved chromatin accessibility profiling offers the potential to investigate gene regulatory processes within the spatial c
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Stegle Lab @steglelab.bsky.social · 19/07/2025
@thbec.bsky.social is going to share preliminary results on Meta-DeepRVAT, a new approach for deep learning based meta-analysis improving the power of rare variant association studies using population scale external control cohorts. #MLCSB 📅 July 21 |📍 Poster A-312
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Kipoi @kipoizoo.bsky.social · 28/05/2025
Join us for our next Kipoi Seminar with Katherine Pollard, Gladstone Institute of Data Science & Biotechnology,UCSF, Biohub @gladstoneinst.bsky.social @czbiohub.bsky.social 👉Human variant interpretation with sequence-to-activity models 📅Wed June 4,5:30pm CET🧬 kipoi.org/seminar/🦋@kipoizoo.bsky.social
kipoi.org
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Shubhankar Londhe @slondhe.bsky.social · 25/05/2025
Excited to present at #eshg2025. Catch my talk on improving rare variant association studies using functional gene embeddings, on Monday at 11:45am (C26.06).
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Eva Holtkamp @evaholtkamp.bsky.social · 25/05/2025
Excited to be back at #eshg2025! Come by my poster today to check out fresh results on how rare high impact variants influence gene expression across immune cells—analyzed in 5,000 UK Biobank participants
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Gagneur lab @gagneurlab.bsky.social · 06/03/2025
Tomorrow Johannes Hingerl @johahi.bsky.social gives a talk on scooby at #probgen25. Enjoy learning in the legendary CSHL auditorium how to model RNA-seq and ATAC-seq profiles in individual cells from half a megabase of genomic sequence. Preprint: doi.org/10.1101/2024...
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Gagneur lab @gagneurlab.bsky.social · 19/02/2025
Excited to share that PROTRIDER, our method to call outliers on mass spectrometry-based proteomics data, is out now!! #proteomics #massspectrometry #raredisease doi.org/10.1101/2025...
doi.org
PROTRIDER: Protein abundance outlier detection from mass spectrometry-based proteomics data with a conditional autoencoder
Motivation Detection of gene regulatory aberrations enhances our ability to interpret the impact of inherited and acquired genetic variation for rare disease diagnostics and tumor characterization. Wh...
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Kipoi @kipoizoo.bsky.social · 03/02/2025
Join us for our next Kipoi Seminar with with Pedro Tomaz da Silva @pedrotomazdasilva.bsky.social @gagneurlab.bsky.social @TU_Muenchen! 👉Nucleotide dependency analysis of DNA language models reveals genomic functional elements 📅Wed Feb 5, 5:30pm CET 🧬https://kipoi.org/seminar/ 🦋kipoizoo.bsky
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Gagneur lab @gagneurlab.bsky.social · 23/12/2024
Hey reg genomics folks, here is our little x-mas present: Flashzoi. Borzoi. Just as good. 3x faster. Thumbs up to @johahi.bsky.social for the great initiative, conception & implementation. Big thanks to Johannes Linder, David Kelley and colleagues to have created Borzoi and shared it freely.
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