Ripke Lab for Statistical Genetics

1/ 🧵 For 10+ years, the Schizophrenia Working Group of the PGC has been dedicated to understanding the genetic risk factors for schizophrenia.

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.

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

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...

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!

Article screenshot of a genome-wide association study of major depression published in the journal Cell

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 🧵:

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.

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...

Thanks for the valued colleague award @pgcgenetics.bsky.social, which traveled all the way from Singapore to Berlin!

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...

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...