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New interactive visualisation tool! Plot and Play with multi- and single-trait fine-mapping results – view potential causal variants that are shared or distinct between traits Feng Zhou Adam Butterworth MRC Biostatistics Unit BHF Cardiovascular Epidemiology Unit at Cambridge github.com/fz-cambridge/f… biorxiv.org/cgi/content/sh… 1/4

Excited to share that our interactive visualisation tool for fine-mapping, flashfm-ivis, is out in Bioinformatics academic.oup.com/bioinformatics… Feng Zhou Adam Butterworth MRC Biostatistics Unit BHF Cardiovascular Epidemiology Unit at Cambridge Plot and Play! View potential causal variants that are shared or distinct between traits

A graphical abstract will be available in next week. :)

Three easy steps to use the flashfm-ivis web tool, as mentioned in our recent Bioinformatics paper academic.oup.com/bioinformatics…

New all-in-one web tool!!! Explore and fine-map GWAS signals of traits in UK Biobank with many user-controlled features. See: github.com/fz-cambridge/f… Preprint at: biorxiv.org/cgi/content/sh… Feng Zhou Adam Butterworth MRC Biostatistics Unit BHF Cardiovascular Epidemiology Unit at Cambridge

BSU researchers Feng Zhou and Jennifer Asimit have made video tutorials of how to use their R shiny apps and flashfm-ivis software. Fine-mapping of multiple quantitative traits. Watch videos here 👇 youtube.com/@fz-cambridge4…

Excited to introduce our new multi-group multi-trait fine-mapping method, MGflashfm It jointly fine-maps association signals from multiple traits and population groups Feng Zhou, Opeyemi Soremekun, Tinashe Chikowore, Segun Fatumo, Inês Barroso, Andrew Morris MRC Biostatistics Unit

Fantastic news! We used multi-trait approaches to identify additional loci associated with lipids traits (MTAG) and refine 99% credible sets (flashfm) in 125,000 individuals of African ancestry Abram Kamiza, Sounkou Touré, Feng Zhou, Tinashe Chikowore, Segun Fatumo MRC Biostatistics Unit

Excited to share that our new multi-group multi-trait #finemapping method MGflashfm, that uses #GWAS summary statistics, has been published online at Nature Communications Feng Zhou, Opeyemi Soremekun, Tinashe Chikowore, Segun Fatumo, Inês Barroso, Andrew Morris MRC Biostatistics Unit rdcu.be/dqK8J

Happy to share env-MR-MEGA - first in our suite of environment-adjusted #GWAS methods Use summary-level data to quantify environmental and ancestral heterogeneity Amazing teamwork with Siru_Wang, Oyesola, Abram Kamiza, Michele Ramsay, Andrew Morris, Tinashe Chikowore, Segun Fatumo

Improved genetic discovery and fine-mapping resolution through multivariate latent factor analysis of high-dimensional traits biorxiv.org/cgi/content/sh… #biorxiv_genetic

New preprint - genetic analyses of latent factors from high-dimensional traits give enhanced power for #GWAS discovery and #finemapping Highest gains are through multi-trait fine-mapping of latent factors - we introduce flashfmZero Feng Zhou, William Astle, Adam Butterworth