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Ripke Lab for Statistical Genetics

@ripkelab.bsky.social
87 followers 42 following 1 posts

This is the official Bluesky account of the Ripke Lab for Statistical Genetics @ Charité Berlin. psychiatrie-psychotherapie.charite.…

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Reposted by Ripke Lab for Statistical Genetics
Julius Upmeier zu Belzen @juliusuzb.bsky.social · 05/08/2026
🧬 New preprint! An interpretable omnigenic neural network architecture for the human genome We introduce the Omnigenic Model (OGM), a neural network architecture for human genetics. It uses biological system structure to aggregate genetic variation for disease risk prediction.
doi.org
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Reposted by Ripke Lab for Statistical Genetics
Psychiatric Genomics Consortium (PGC) @pgcgenetics.bsky.social · 17/09/2025
1/ 🧵 For 10+ years, the Schizophrenia Working Group of the PGC has been dedicated to understanding the genetic risk factors for schizophrenia.
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Reposted by Ripke Lab for Statistical Genetics
Alice Braun @alicebraun.bsky.social · 12/03/2025
The Ripke lab has worked on a new stable release of RICOPILI! Updates include compatibility with GRCh38 and imputation using Minimac4. A software tarball and YAML file are provided to help resolve dependency issues: github.com/Ripkelab/ric... Any feedback is highly welcome! @pgcgenetics.bsky.social
github.com
GitHub - Ripkelab/ricopili: Main ricopili repo for public releases
Main ricopili repo for public releases. Contribute to Ripkelab/ricopili development by creating an account on GitHub.
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Reposted by Ripke Lab for Statistical Genetics
Marijn Schipper @mjschipper.bsky.social · 11/02/2025
Incredibly proud to see our latest work out in Nature Genetics: www.nature.com/articles/s41... Here we share our FLAMES framework, which predicts the effector genes in GWAS loci with state-of-the-art precision🔥 Special thanks to @daniposthu.bsky.social A full thread describing findings below!
rdcu.be
Prioritizing effector genes at trait-associated loci using multimodal evidence
Nature Genetics - FLAMES is a machine learning approach combining variant fine-mapping, SNP-to-gene annotations and convergence-based gene prioritization scores to identify candidate effector genes...
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Reposted by Ripke Lab for Statistical Genetics
Psychiatric Genomics Consortium (PGC) @pgcgenetics.bsky.social · 14/01/2025
1/n Our multi-ancestry #GWAS meta-analysis of major depression is now published in @cellpress.bsky.social. www.cell.com/cell/fulltex... A thread 🧵:
Article screenshot of a genome-wide association study of major depression published in the journal Cell
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Reposted by Ripke Lab for Statistical Genetics
Mark James Adams @markjamesadams.bsky.social · 14/01/2025
New study from the @pgcgenetics.bsky.social: Multi-ancestry GWAS of MDD in over half a million cases and 4 million controls. www.cell.com/cell/fulltex...
cell.com
Trans-ancestry genome-wide study of depression identifies 697 associations implicating cell types and pharmacotherapies
Trans-ancestry GWAS of major depression identifies 697 genetic variants and 308 genes, implicating neural and molecular mechanisms and drug repurposing opportunities.
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Ripke Lab for Statistical Genetics @ripkelab.bsky.social · 03/12/2024
Thanks for the valued colleague award @pgcgenetics.bsky.social, which traveled all the way from Singapore to Berlin!
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Reposted by Ripke Lab for Statistical Genetics
Fabian Streit @fstreit.bsky.social · 15/11/2024
Happy to see this finally online: we investigated the genetic association signal of Borderline Personality Disorder in a GWAS meta-analysis with >12,000 cases. We identified 6 risk loci, and investigated shared genetic risk using genetic correlations and PheWAS www.medrxiv.org/content/10.1...
medrxiv.org
Genome-wide association study of borderline personality disorder identifies six loci and highlights shared risk with mental and somatic disorders
Environmental and genetic risk factors contribute to the development of borderline personality disorder (BPD). We conducted the largest GWAS of BPD to date, meta-analyzing data from 12,339 cases and 1...
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