Mihaly Badonyi
@mbadonyi.bsky.social
87 followers 290 following 49 posts
postdoc @uoe-igc.bsky.social computational biology | disease genetics
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mbadonyi.bsky.social
1/8 Our new paper in Nature Communications explores how often pathogenic missense variants cause disease through loss-of-function (LOF), gain-of-function (GOF), or dominant-negative (DN) effects.
📄 nature.com/articles/s41...
mbadonyi.bsky.social
3/3 Our study also introduces a simple structural metric, SPDV, proposed as an orthogonal strategy to existing computational tools for aiding the diagnosis of RyR1-related diseases. If you are interested in applying this metric to other proteins, check out Lukas’ Colab notebook:
💻 edin.ac/40yke9l
Google Colab
edin.ac
mbadonyi.bsky.social
2/3 If you work on MAVEs, or are a clinician curious about how strong MAVE or VEP evidence is in a gene, check out 𝚊𝚌𝚖𝚐𝚜𝚌𝚊𝚕𝚎𝚛. It calibrates functional scores to #ACMG/AMP standard, and you can run it via this Colab notebook:
💻 colab.research.google.com/github/badon...
Google Colab
colab.research.google.com
mbadonyi.bsky.social
1/3 In this work on RyR1, led by Rolando, we (@marshlab.bsky.social) highlight the limitations of using ROC AUC alone to assess clinical utility. Future approaches should consider classification behaviour across the full score distribution.
📄 onlinelibrary.wiley.com/doi/epdf/10....
Complementary Roles of Structure and Variant Effect Predictors in RyR1 Clinical Interpretation
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onlinelibrary.wiley.com
Reposted by Mihaly Badonyi
ee-reh-neh.bsky.social
I'm stoked to be organising next year's MSS right here in beautiful Melbourne! We know Australia is very far away, and we're working hard to make sure we can support as many ECRs to attend as possible, so please do register and apply for a travel award!
varianteffect.bsky.social
📣Call for Abstracts
for the Mutational Scanning Symposium! #VariantEffect26
🗓️ March 25-27, 2026
📍 Melbourne, Australia (and online!)
📝 Submit your abstract (deadline is Nov 2nd, 2025!)
➡️ Registration is also now open!!
ℹ️ www.mss2026.org

#FunctionalGenomics #Symposium #Australia #CallForAbstracts
mbadonyi.bsky.social
Thanks also to @natcomms.nature.com for the smooth review process!
mbadonyi.bsky.social
8/8 Our work raises many interesting questions, but I will leave you with one: when a disease can be caused by both dominant and recessive mutations, how can we predict which variants are pathogenic only in the recessive state?
mbadonyi.bsky.social
7/8 Finally, we made it easy to compute mLOF for a set of missense variants: there is a user-friendly Google Colab notebook available for anyone to try.
💻 edin.ac/48Aysep
Google Colab
edin.ac
mbadonyi.bsky.social
6/8 We also find that many genes can cause different diseases through different mechanisms. This carries an important message for therapeutic development, suggesting that different phenotypes of the same gene may need distinct treatment strategies.
mbadonyi.bsky.social
5/8 Therefore, we applied mLOF to 2,837 phenotypes across 1,979 Mendelian disease genes. In dominant genes, nearly half of phenotypes appear to arise from non-LOF mechanisms.
mbadonyi.bsky.social
4/8 Perhaps the most powerful validation of mLOF lies in multiplexed assays of variant effect #MAVE data. LOF, DN, GOF, and hyper-complementing variants identified by MAVEs are distinguished consistently and effectively by the mLOF score.
mbadonyi.bsky.social
3/8 We introduce a protein structure-based missense LOF (mLOF) likelihood score, which predicts if mutations lead to LOF based on how much they cluster in structures and how energetically destabilising they are.
mbadonyi.bsky.social
2/8 Knowledge of mechanisms is hugely important for treating genetic diseases: LOF mutations can usually be treated with gene replacement, but other mechanisms often require more targeted approaches.
mbadonyi.bsky.social
1/8 Our new paper in Nature Communications explores how often pathogenic missense variants cause disease through loss-of-function (LOF), gain-of-function (GOF), or dominant-negative (DN) effects.
📄 nature.com/articles/s41...
mbadonyi.bsky.social
Yes, if vaccines count as a discovery, I would add the Haber-Bosch process for producing ammonia, and by extension, fertiliser to feed the world.
mbadonyi.bsky.social
In the previous version, I found the functionality where hovering over the sequence highlighted the corresponding residue in the structure to be very useful. Any chance this could be brought back while keeping the `copy sequence` button?
Reposted by Mihaly Badonyi
biorxivpreprint.bsky.social
Why variant effect predictors and multiplexed assays agree and disagree https://www.biorxiv.org/content/10.1101/2025.07.31.667868v1
Reposted by Mihaly Badonyi
biorxivpreprint.bsky.social
A knowledge-based distance metric highlights underperformance of variant effect predictors on gain-of-function missense variants https://www.biorxiv.org/content/10.1101/2025.07.23.666325v1
Reposted by Mihaly Badonyi
wbickmor.bsky.social
GWAS to mechanism: when non-coding is coding. Beautiful insightful science from @gweykopf.bsky.social @simonbiddie.bsky.social Joe Marsh and many colleagues. @uoe-igc.bsky.social @cmvm-edinburghuni.bsky.social www.biorxiv.org/content/10.1...
mbadonyi.bsky.social
We are working to update the manuscript with additional analyses that support the use of as few as 10 pathogenic and benign labels.

Both the R package and the Colab will soon receive small updates that improve interpretability and score threshold determination.
mbadonyi.bsky.social
Thanks to #CCG2025 for the opportunity to present our work on `acmgscaler`, a standardised tool to convert functional scores into ACMG/AMP evidence strengths.
#rstats
You can try out the Colab notebook and the R package here: https://github.com/badonyi/acmgscaler