If you are interested in high-throughput calibration, take a look at the acmgscaler R package:
cran.r-project.org/web/packages...
Or plug in your MAVE or VEP of interest to our Colab:
colab.research.google.com/github/badon...
Pinc is now available as a C program, eliminating interpreter overhead and substantially speeding up computation for large-scale structural analyses. It’s still under active development, so please reach out with any questions, feedback, or issues. 🔗 git.mpi-cbg.de/tothpetroczy...
#alphafold
As we move towards a complete map of human variant effects, evaluating VEP and MAVE scores in clinically meaningful ways becomes essential. In work led by Yifei Shang and @jmarshlab.bsky.social, we explore mean evidence strength (MES) to quantify clinical utility after ACMG/AMP calibration.
Having just taken this course, I highly recommend it.
Great inaugural lecture by Joe. Honoured to see some of our joint work mentioned.
Provides a function to calibrate variant effect scores against evidence strength categories defined by the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pa...
Grateful to @mpi-cbg.de @csbdresden.bsky.social @mpipks.bsky.social for a fantastic work environment (and my ELBE fellowship).
Based on this, we introduce Pinc (“probability of interface native contacts”): a simple and interpretable protein-protein interaction score for #alphafold (AF2/AF3) models.
Colab + CLI: git.mpi-cbg.de/tothpetroczy...
Feedback is appreciated.
#rstats
