pengfeiDong

Excited to share #AlphaGenome, a start of our AlphaGenome named journey to decipher the regulatory genome! The model matches or exceeds top-performing external models on 24 out of 26 variant evaluations, across a wide range of biological modalities.1/6

Excited to share our latest review in @TrendsGenetics cell.com/trends/genetic…

GET is finally published! - Paper: t.ly/iQct_ (new validations, dry and wet) - Model: t.ly/4jnUI (new tutorial on PBMC 10x Multiome data) - Analysis package: t.ly/OqLAL - Demo: t.ly/rbFQB - Docker: t.ly/86n_i

@alexanderfuxi Congrats!

🧠 New brain atlas reveals region-specific gene regulation & promoter-isoform insights, advancing neuropsychiatric disorder research & genetic fine-mapping. #Genomics #Neuroscience #cdneurogenomics #roussoslab Read more in #NatureCommunications rdcu.be/d06ta

🎉 Excited to announce preprints from the first #PsychAD package! Check out details of our work at Psych-AD.org 🧵 Found out summary of papers below👇

The Center for Disease Neurogenomics (CDN) had a successful retreat day. The year 2024 marked the 10-year anniversary of the lab, and we have grown to 67 members. #CDN #retreat

We are thrilled to share a preprint on human myeloid cells and AD. Collaboration with @panos_roussos @FullardJohn @ChrisAPorras @collin_spencer_ @MilosPjanic @PhilippWeiler7 and many others.

Please check out the preprint of our lab's new single-cell software, Dreamlet, a faster, memory-efficient statistical model for large-scale single-cell differential expression analysis.

@Bun_Without_B no problem. I think you can derive this information from synapse.org/#!Synapse:syn3…

@PengfeiD Thank you @PengfeiD ! Sorry to bother you again but is there a binary table somewhere that has all the ATAC peaks and whether they are considered "active" in a cell type/ brain region? Similar to the table where you compare the Jaccard index between your data with the reference.

Excited to share our recent preprint with multi-regional RNAseq and ATACseq profilings to explore the differences among brain regions and better understand disease heritability. @panos_roussos @LabRoussos biorxiv.org/content/10.110….

@XiaotaoWang3 Thanks!

@PengfeiD @NatureGenet @LabRoussos Congrats!

Thrilled to share our study in @NatureGenet on population-level analysis of transcribed enhancers. Thanks to my colleagues at @LabRoussos and reviewers for helping to improve it. nature.com/articles/s4158…

@Bun_Without_B Thanks, An. The table and DEG results are available at synapse.org/#!Synapse:syn3….

@PengfeiD @panos_roussos @LabRoussos amazing paper! We are working on sth similar but using H3K27ac (less samples, less brain regions), would love to access your supplementary data so we can compare our results with yours and cite you. How do I obtain the RNA-seq/ATAC-seq final table and list of differential peaks?

@LindsayRizzardi @panos_roussos @LabRoussos Thanks for sharing the two manuscripts very interesting works!

@PengfeiD @panos_roussos @LabRoussos Great work! This is very consistent with our analyses of DNA methylation (and accessibility/transcription) from sorted neurons across 8 cortical/basal/midbrain regions in up to 20 donors. pubmed.ncbi.nlm.nih.gov/30643296/ pubmed.ncbi.nlm.nih.gov/33888138/

We found a promoter co-accessibility module that is robustly associated with the common variants of ASD, BD, and SCZ. More importantly, the enrichment is independent of reported cell type-specific gene expression and annotated schizophrenia-susceptible pathways.

We identified an enhancer chromatin co-accessibility that exhibits a >50 times per SNP heritability than the baseline model for SCZ common risk variants, and the genes are strongly associated with different subclasses of SCZ susceptible pathways.