2) larger eQTL datasets found more colocalisations and enable the detection of lower MAF eQTLs but 3) higher resolution eQTLs identified in single-cell datasets are more likely to colocalise.
Jeffrey Pullin
1) with current data we can colocalise a substantial fraction of GWAS signals: 34% in the IMD/immune cell analysis and 50% in OpenTargets. GWAS signals that were closer to genes and were more common were more likely to colocalise
Overall, we see large, single-cell studies as crucial for closing the colocalisation gap. We also noticed that many GWAS signals colocalise with multiple eQTLs, and further analyses suggested that this is due to co-regulation. Check out the paper for all the details!
This work was led by @greales7.bsky.social and supervised by @chr1sw.bsky.social and Elena Vigorito!
Jeffrey Pullin
Jeffrey Pullin
tinyurl.com/reuxynmc Very excited to see this work I was a small part of published! We analysed two large scale colocalisation datasets: OpenTargets data and an analysis of immune-mediated disease GWAS/immune cell eQTLs seeking to understand the "colocalisation gap". Some highlights:
tinyurl.com/reuxynmc Very excited to see this work I was a small part of published! We analysed two large scale colocalisation datasets: OpenTargets data and an analysis of immune-mediated disease GWAS/immune cell eQTLs seeking to understand the "colocalisation gap". Some highlights:
Jeffrey Pullin
My last piece of work at the Wallace group. Please check it out and let us know what you think! 😀Thanks @jeffreypullin.bsky.social for summarising it!
Author summary Most of the genetic variants associated with complex traits are located outside genes, limiting functional interpretation. Genetic colocalisation helps identify candidate causal genes b...
journals.plos.org
Author summary Most of the genetic variants associated with complex traits are located outside genes, limiting functional interpretation. Genetic colocalisation helps identify candidate causal genes b...
Super excited to see this out! Fantastic collaboration with Luke O'Connor and trainees Amber Shen and Xinran Wang.
Thread with details will come soon, but linear ARG provide a HIGHLY efficient representation of genotype data that can be treated as a linear operator
www.biorxiv.org/content/10.6...
Out now in Nature!
Genetic analysis of the largest single-cell dataset of Inflammatory Bowel Disease (IBD)-relevant tissues nominates effector genes and cell types at over half of known IBD loci, including 74 for which this is the first candidate effector gene 🖥️🧬
www.nature.com/articles/s41...
Jeffrey Pullin
www.biorxiv.org
Single-cell mapping of cis-expression quantitative trait loci in inflammatory bowel disease revealed distal, enhancer-enriched variants detected at the cell-type level more frequently co-loc...
Excited to share this new preprint from a large collaborative effort using #exome + #genome sequencing, moving beyond GWAS to implicate 68 genes in #IBD through rare protein-coding variation.
bit.ly/43h72GA
@broadinstitute.org
@mgbresearch.bsky.social
