Jeffrey Pullin

Jeffrey Pullin

@jeffreypullin.bsky.social

PhD Student, MRC Biostatistics Unit University of Cambridge Gates Cambridge Scholar Bioinformatics, genetics, single-cell, statistics Australian 🇦🇺

201 followers323 following52 posts

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Jeffrey Pullin
@jeffreypullin.bsky.social

Very excited to share new work from my PhD on a new software package for eQTL mapping: quasar. The quasar software package is a C++ program designed to provide a flexible and efficient eQTL mapping. www.medrxiv.org/content/10.1...

medrxiv.orgFlexible and efficient count-distribution and mixed-model methods for eQTL mapping with quasarIdentifying genetic variants that affect gene expression, expression quantitative trait loci (eQTLs), is a major focus of modern genomics. Today, various methods exist for eQTL mapping, each using dif...

Jeffrey Pullin reposted

Nikhil Milind
@nikhilmilind.dev

I'll be at #ASHG2026 this year! I'm presenting some recent work (with @huishengzhu.bsky.social) on extracting all the information we can out of rare-variant burden test statistics for downstream meta-analysis. Catch me at poster 8357F to talk about the project or stat gen / pop gen.

Jeffrey Pullin reposted

Jeffrey Pullin
@jeffreypullin.bsky.social

Very excited to be heading to Montreal for #ASHG26 next week! Come find me at poster board 8448F to talk about scalable single-cell eQTL mapping

Jeffrey Pullin reposted

Open Targets
@opentargets.org

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...

nature.comCell-type-resolved genetic variation shapes inflammatory bowel disease risk - NatureSingle-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...
Jeffrey Pullin
@jeffreypullin.bsky.social

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!

Jeffrey Pullin
@jeffreypullin.bsky.social

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:

journals.plos.orgDesign and interpretation of eQTL-GWAS colocalisation studies: Lessons from a large-scale evaluationAuthor 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...
Jeffrey Pullin
@jeffreypullin.bsky.social

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

Jeffrey Pullin
@jeffreypullin.bsky.social

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 reposted

Guillermo Reales
@greales7.bsky.social

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!

Jeffrey Pullin@jeffreypullin.bsky.social

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:

journals.plos.orgDesign and interpretation of eQTL-GWAS colocalisation studies: Lessons from a large-scale evaluationAuthor 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...

Jeffrey Pullin reposted

Jeffrey Pullin
@jeffreypullin.bsky.social

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:

journals.plos.orgDesign and interpretation of eQTL-GWAS colocalisation studies: Lessons from a large-scale evaluationAuthor 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...

Jeffrey Pullin reposted

thexavierlab.bsky.social
@thexavierlab.bsky.social

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

bit.lyExome sequencing directly implicates 68 genes in inflammatory bowel diseaseInflammatory bowel disease (IBD) is a chronic immune-mediated disorder of the gastrointestinal tract whose genetic basis is only partly resolved because most risk variants identified by genome-wide as...

Jeffrey Pullin reposted

David Ochoa
@d0choa.bsky.social

🧬 New preprint: "The Human Pleiotropic Map of GWAS Associations and Therapeutic Implications" Why do some genetically supported drug targets succeed in the clinic while others fail? Across 100,526 GWAS, the same evidence flags constrained gene functions rarely safe to modulate.

Jeffrey Pullin reposted

David Ochoa
@d0choa.bsky.social

The Open Targets Platform spring 🌼 release is out — and this one marks the beginning of something we've been building towards for a while.

Jeffrey Pullin reposted

Patrick Gibbs
@patrickgibbs.bsky.social

Happy to share new manuscript I completed with @ee-reh-neh.bsky.social & @davisjmcc.bsky.social back in Melbourne. The work originally conceived by @ijbeasley.bsky.social focuses on how we can reconcile and meta-analyse eQTL studies across studies cohorts and ancestries. doi.org/10.64898/202...

doi.orgPower is a major confounder in the analysis of cross-ancestry 'portability' in human eQTLsThe phenotypic effects of germline variants are often mediated through gene regulation. Expression quantitative trait loci (eQTLs) are genetic variants associated with changes in gene expression. Understanding how eQTLs vary across populations is essential for characterising the genetic and regulatory drivers of trait diversity. Meta-analysing eQTL studies from multiple populations enables more robust detection of eQTLs and can reveal regulatory mechanisms shaped by population-specific environmental or ancestry-related factors. However, across the multi-ancestry eQTL literature, a wide range of methods have been used to quantify eQTL portability across ancestry groups. Because different studies employ different portability metrics, it is challenging to form a coherent view of the regulatory landscape across populations. In this work, we analyse eQTL summary statistics from ten datasets matched on tissue type and sequencing technology. We compare portability metrics used previously and show that they can yield markedly different patterns of apparent regulatory conservation or divergence. We then examine the statistical determinants of portability across metrics and demonstrate that sample size, minor allele frequency, and linkage disequilibrium are major drivers of the observed differences in eQTL portability across studies. These findings highlight that differences in statistical power stemming from factors such as population size and allele frequency must be accounted for when evaluating eQTL portability. To address this issue, we introduce a new approach designed to correct for these factors when calling eQTL portability. Finally, we show that empirical Bayes multivariate adaptive shrinkage provides a powerful framework for meta-analysing multiple eQTL studies, with the ability to pool signals across populations to produce more robust effect-size estimates within each population. ### Competing Interest Statement The authors have declared no competing interest. National Health and Medical Research Council, https://ror.org/011kf5r70, Ideas Grant 2020501, Investigator Grant 1195595
Irene Gallego Romero@ee-reh-neh.bsky.social

Finally, today's offering! www.biorxiv.org/content/10.6... This began life as a very different project which failed because we couldn't agree on defining eqtl sharing across cohorts. So two young members of the lab dug deeply into this - first @ijbeasley.bsky.social, then @patrickgibbs.bsky.social

biorxiv.orgbiorxiv.org
Jeffrey Pullin
@jeffreypullin.bsky.social

Very excited to see this work be the first to use the quasar method for eQTL mapping!

Irene Gallego Romero@ee-reh-neh.bsky.social

First, a couple of weeks ago: www.biorxiv.org/content/10.6... Single cell RNAseq on blood from 200 donors across 4 sites in Indonesia spanning regional axes of genetic and environmental diversity. This is one of very few scRNA data sets from the Global South, including urban and rural settings.

biorxiv.orgbiorxiv.org

Jeffrey Pullin reposted

Irene Gallego Romero
@ee-reh-neh.bsky.social

Hi yes I will have more to say about this in a few hours but please enjoy this paper. It's been a huge labour of love and effort for the last four years, and a significant part of our research efforts, and I'm so so so thrilled it's finally ready to share. Tldr: scRNA-seq in Indonesia hard but fun

bioRxiv Genomics@biorxiv-genomic.bsky.social

Ancestral and environmental diversity shape the immune landscape in Indonesia https://www.biorxiv.org/content/10.64898/2026.02.15.704933v1

Jeffrey Pullin reposted

Danai Vagiaki
@danaivagiaki.bsky.social

Delighted to present Latent Interaction Variational Inference (LIVI), a framework for trans-eQTL mapping at single-cell resolution that I developed during my PhD together with colleagues from @steglelab.bsky.social 1/n

bioRxiv Genomics@biorxiv-genomic.bsky.social

Mapping trans-eQTLs at single-cell resolution using Latent Interaction Variational Inference. https://www.biorxiv.org/content/10.64898/2026.02.04.703363v1

Jeffrey Pullin reposted

Jonathan Pritchard
@jkpritch.bsky.social

New preprint alert: we use sign errors as a test of how well TWAS works. Very worryingly we find that TWAS gets the sign wrong around 1/3 of the time (compared to 50% for pure guessing). You can read more about our analysis here, and what we think is going on 👇

Nikhil Milind@nikhilmilind.dev

How well does TWAS estimate a gene’s direction of effect on a trait? We think of this as an important stress-test for the accuracy of TWAS. In a new pre-print, we find that TWAS gets the sign wrong around 20-30% of the time! doi.org/10.64898/202... 1/n

doi.orgHigh false sign rates in transcriptome-wide association studiesTranscriptome-wide association studies (TWAS) are widely used to identify genes involved in complex traits and to infer the direction of gene effects on traits. However, despite their popularity, it r...

Jeffrey Pullin reposted

Nikhil Milind
@nikhilmilind.dev

How well does TWAS estimate a gene’s direction of effect on a trait? We think of this as an important stress-test for the accuracy of TWAS. In a new pre-print, we find that TWAS gets the sign wrong around 20-30% of the time! doi.org/10.64898/202... 1/n

doi.orgHigh false sign rates in transcriptome-wide association studiesTranscriptome-wide association studies (TWAS) are widely used to identify genes involved in complex traits and to infer the direction of gene effects on traits. However, despite their popularity, it r...

Jeffrey Pullin reposted

Emma Dann
@emmamarydann.bsky.social

Together with @ronghuizhu.bsky.social, we are thrilled to present our new perturb-seq study of 22M primary CD4+ T cells, across donors and timepoints – the result of a decade-long collaboration between the Marson @marsonlab.bsky.social and Pritchard @jkpritch.bsky.social labs 🧵 tinyurl.com/gwt2025

tinyurl.comGenome-scale perturb-seq in primary human CD4+ T cells maps context-specific regulators of T cell programs and human immune traitsGene regulatory networks encode the fundamental logic of cellular functions, but systematic network mapping remains challenging, especially in cell states relevant to human biology and disease. Here, ...

Jeffrey Pullin reposted

Nick Banovich
@nebanovich.bsky.social

Great new work led by Aaron Kwok from @davisjmcc.bsky.social’s group. A tool to “denoise” contaminating transcripts from image based spatial data. www.biorxiv.org/content/10.1...

biorxiv.orgDenoising image-based spatial transcriptomics data with DenoISTImage-based spatial transcriptomics (IST) technologies provide unprecedented resolution of gene expression in tissue sections, but suffer from contamination of cells' gene expression profiles due to i...

Jeffrey Pullin reposted

loic-yengo.bsky.social
@loic-yengo.bsky.social

First time on Bsky and first big announcement! I am excited to announce that our new study explaining the missing heritability of many phenotypes using WGS data from ~347,000 UK Biobank participants has just been published in @Nature. Our manuscript is here: www.nature.com/articles/s41....

nature.comEstimation and mapping of the missing heritability of human phenotypes - NatureWGS data were used from 347,630 individuals with European ancestry in the UK Biobank to obtain high-precision estimates of coding and non-coding rare variant heritability for 34 co...

Jeffrey Pullin reposted

Stephen Burgess
@stevesphd.bsky.social

New pre-print: "Systematic comparison of colocalization methods using protein quantitative trait loci" led by @hwang_seongwon at www.biorxiv.org/content/10.1.... Which method does best? Find out!

biorxiv.orgSystematic comparison of colocalization methods using protein quantitative trait lociColocalization is frequently performed as a step to triage findings from genetic investigations linking molecular and disease data. However, the reliability and consistency of the various colocalizati...

Jeffrey Pullin reposted

Chris Wallace
@chr1sw.bsky.social

New: GWAS of serurm antibody levels. Interesting findings include genetically correlated traits with hard-to-find shared causal variants, and apparently genetically uncorrelated traits sharing causal variants that operate in inconsistent directions www.medrxiv.org/content/10.1...

medrxiv.orgLarge-scale GWAS meta-analysis of serum antibody levels reveals distinct genetic architecturesAntibodies are the principal effector proteins of humoral immunity. Dysregulated antibody production is a feature of a number of heritable immune-mediated diseases, such as the antibody deficiencies a...

Jeffrey Pullin reposted

Open Targets
@opentargets.org

Out now in Nature Comms: the largest trans-eQTL meta-analysis in a single cell type! An Open Targets team led by Krista Freimann and @kauralasoo.bsky.social analysed 3,734 lymphoblastoid cell line samples across nine cohorts, identifying four robust loci www.nature.com/articles/s41...

linkedin.comTrans-eQTL mapping prioritises USP18 as a negative regulator of interferon response at a lupus risk locus - Nature Communications | Open TargetsOut now in Nature Comms: the largest trans-eQTL meta-analysis in a single cell type! An Open Targets team led by Krista Freimann and Kaur Alasoo analysed 3,734 lymphoblastoid cell line samples across...

Jeffrey Pullin reposted

wcrismani.bsky.social
@wcrismani.bsky.social

I feel incredibly privileged to share this study on Fanconi anaemia, based on a small but important cohort. This work describes the genetics and clinical outcomes of patients in Australia and New Zealand with a diagnosis of FA. www.sciencedirect.com/science/arti...

sciencedirect.comClinical and genetic spectrum of Fanconi anemia in Australia and New ZealandFanconi anemia (FA) is a rare genetic condition that predisposes to progressive bone marrow failure, a specific spectrum of malignancies, including he…

Jeffrey Pullin reposted

Peter Kraft
@peter-kraft.bsky.social

Multi-ancestry GWAS can increase power and precision, but how should we analyze them? Pooled or stratified? We answer that question in a paper out today in AJHG, led by Julie Dias and Haoyu Zhang. 1/7 www.cell.com/ajhg/fulltex...

cell.comEvaluating multi-ancestry genome-wide association methods: Statistical power, population structure, and practical implicationsMulti-ancestry GWASs enhance discovery in diverse populations, but optimal methods remain debated. Using theory, simulations, and analyses from the UK Biobank and All of Us, we show that pooled analys...

Jeffrey Pullin reposted

Angli Xue
@anglixue.bsky.social

New preprint alert: tinyurl.com/tenk10k-multiome. Excited to share our analysis on the impact of genetic variants on single-cell chromatin accessibility in blood, using scATAC-seq and WGS from over 1,000 donors and 3.5M nuclei as part of TenK10K phase 1 🧬 🧵👇 (1/n)

tinyurl.comGenetic regulation of cell type-specific chromatin accessibility shapes immune function and disease riskUnderstanding how genetic variation influences gene regulation at the single-cell level is crucial for elucidating the mechanisms underlying complex diseases. However, limited large-scale single-cell multi-omics data have constrained our understanding of the regulatory pathways that link variants to cell type-specific gene expression. Here we present chromatin accessibility profiles from 3.5 million peripheral blood mononuclear cells (PBMCs) across 1,042 donors, generated using single-cell ATAC-seq and multiome (RNA+ATAC) sequencing, with matched whole-genome sequencing, generated as part of the TenK10K program. We characterized 440,996 chromatin peaks across 28 immune cell types and mapped 243,273 chromatin accessibility quantitative trait loci (caQTLs), 60% of which are cell type-specific. Integration with TenK10K scRNA-seq data (5.4 million PBMCs) identified 31,688 candidate cis-regulatory elements colocalized with eQTLs; over half (52.5%) show evidence of causal effects mediated via chromatin accessibility. Integrating caQTLs with GWAS summary statistics for 16 diseases and 44 blood traits uncovered 9.8% - 30.0% more colocalized signals compared with using eQTLs alone, many of which have not been reported in prior studies. We demonstrate cell type-specific mechanisms, such as a regulatory effect on IRGM acting through altered promoter chromatin accessibility in CD8 effector memory T cells but not in naive cells. Using a graph neural network, we inferred peak-to-gene relationships from unpaired multiome data by incorporating caQTL and eQTL signals, achieving up to 80% higher accuracy compared to using paired multiome data without QTL information. This improvement further enhanced gene regulatory network inference, leading to the identification of 128 additional transcription factor (TF)-target gene pairs (a 22% increase). These findings provide an unprecedented single-cell map of chromatin accessibility and genetic variation in human circulating immune cells, establishing a powerful resource for dissecting cell type-specific regulation and advancing our understanding of genetic risk for complex diseases. ### Competing Interest Statement L.C., E.B.D., and K.K.H.F. are employed at Illumina Inc. D.G.M. is a paid advisor to Insitro and GSK, and receives research funding from Google and Microsoft, unrelated to the work described in this manuscript. G.A.F reports grants from National Health and Medical Research Council (Australia), grants from Abbott Diagnostic, Sanofi, Janssen Pharmaceuticals, and NSW Health. G.A.F reports honorarium from CSL, CPC Clinical Research, Sanofi, Boehringer-Ingelheim, Heart Foundation, and Abbott. G.A.F serves as Board Director for the Australian Cardiovascular Alliance (past President), Executive Committee Member for CPC Clinical Research, Founding Director and CMO for Prokardia and Kardiomics, and Executive Committee member for the CAD Frontiers A2D2 Consortium. In addition, G.A.F serves as CMO for the non-profit, CAD Frontiers, with industry partners including, Novartis, Amgen, Siemens Healthineers, ELUCID, Foresite Labs LLC, HeartFlow, Canon, Cleerly, Caristo, Genentech, Artyra, and Bitterroot Bio, Novo Nordisk and Allelica. In addition, G.A.F has the following patents: "Patent Biomarkers and Oxidative Stress" awarded USA May 2017 (US9638699B2) issued to Northern Sydney Local Health District, "Use of P2X7R antagonists in cardiovascular disease" PCT/AU2018/050905 licensed to Prokardia, "Methods for treatment and prevention of vascular disease" PCT/AU2015/000548 issued to The University of Sydney/Northern Sydney Local Health District, "Methods for predicting coronary artery disease" AU202290266 issued to The University of Sydney, and the patent "Novel P2X7 Receptor Antagonists" PCT/AU2022/051400 (23.11.2022), International App No: WO/2023/092175 (01.06.2023), issued to The University of Sydney. ### Funding Statement A.X. is supported by NHMRC Investigator grant 2033018. J.E.P. is supported by NHMRC Investigator grant 2034556, and a Fok Family Fellowship; D.G.M. is supported by an NHMRC investigator grant (2009982). G.A.F. and the BioHEART Study have been supported by NHMRC Investigator Grant, NSW Health Office of Health and Medical Research, and the NSW Health Statewide Biobank scheme. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Human Research Ethics Committee of St Vincent's Hospital gave ethical approval for this work. The National Statement on Ethical Conduct in Human Research of the National Health and Medical Research Council gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Raw caQTL summary statistics will be available at Zenodo website prior to acceptance. [https://github.com/powellgenomicslab/tenk10k\_phase1\_multiome][1] [1]: https://github.com/powellgenomicslab/tenk10k_phase1_multiome

Jeffrey Pullin reposted

mihkeljesse.bsky.social
@mihkeljesse.bsky.social

After 1.5 years of work in @kauralasoo.bsky.social’s lab, we finally published my preprint! We introduce gpu-coloc, a GPU-accelerated implementation of coloc, show comparability to CLPP and aim to provide practical guidelines. Now accessible on BioRxiv: www.biorxiv.org/content/10.1...

biorxiv.orgUltra-fast genetic colocalisation across millions of traitsColocalisation is a powerful approach to assess if two genetic association signals are likely to share a causal variant. However, association analyses in large biobanks and molecular quantitative trai...

Jeffrey Pullin reposted

Andrew Bass
@ajbass.bsky.social

Excited to see our (w/ @chr1sw.bsky.social) work published in @natcomputsci.nature.com! We developed a new framework, surrogate functional false discovery rate (sffdr), that integrates summary statistics of related traits to improve power in GWASs. Paper: www.nature.com/articles/s43...

nature.comExploiting pleiotropy to enhance variant discovery with functional false discovery rates - Nature Computational ScienceThis study introduces a cost-effective strategy called surrogate functional false discovery rates to increase power in genome-wide association studies by leveraging genetic correlations (or pleiotropy...

Jeffrey Pullin reposted

alexblakes.bsky.social
@alexblakes.bsky.social

I am absolutely delighted to share our work describing a new *recessive* condition caused by variants in #RNU4-2. Yes, that #RNU4-2! tinyurl.com/3j9r56s8 @rociorius.bsky.social @yuyangchen.bsky.social @gregfindlay.bsky.social @dgmacarthur.bsky.social @cassimons.bsky.social @nickywhiffin.bsky.social

medrxiv.orgBiallelic variants in the non-coding RNA gene RNU4-2 cause a recessive neurodevelopmental syndrome with distinct white matter changesGenetic variants in RNU4-2, which encodes U4, a key non-coding small nuclear RNA (snRNA) component of the major spliceosome, were recently shown to cause a prevalent neurodevelopmental disorder (NDD) ...

Jeffrey Pullin reposted

Michael Love
@mikelove.bsky.social

Excited to share this preprint from first author Jon Rosen, a postdoctoral fellow in the @klmohlke.bsky.social lab and my lab. We examine eQTL study sample size and how this affects signal discovery and rates of colocalization with GWAS. www.biorxiv.org/content/10.1...

biorxiv.orgHigher eQTL power reveals signals that boost GWAS colocalizationExpression quantitative trait locus (eQTL) studies in human cohorts typically detect at least one regulatory signal per gene, and have been proposed as a way to explain mechanisms of genetic liability...

Jeffrey Pullin reposted

Kerstin Ludwig
@kuludwig.bsky.social

🔔Paper alert! Extremely excited to share a preprint from our lab! Spearheaded by @axel-schmidt.bsky.social, a super talented medical & computational geneticist, we studied latent Epstein-Barr virus (EBV) infection at population-scale. Interested in how this works & what we found? Read along! 👇

medRxivpreprint@medrxivpreprint.bsky.social

Host control of latent Epstein-Barr virus infection https://www.medrxiv.org/content/10.1101/2025.07.19.25331823v1

Jeffrey Pullin reposted

Nicholas Mancuso
@nmancuso.bsky.social

Super excited to see this out. What started as some math in a grant in 2020, to a student deciding to take this on in 2022, to published in 2025. These things can take time and patience is key!

Nature Genetics@natgenet.nature.com

📢OUT TODAY @natgenet.nature.com 📰Improved multiancestry fine-mapping identifies cis-regulatory variants underlying molecular traits and disease risk. By @zeyunlu.bsky.social, @nmancuso.bsky.social and colleagues. ⬇️ www.nature.com/articles/s41...

nature.comImproved multiancestry fine-mapping identifies cis-regulatory variants underlying molecular traits and disease risk - Nature GeneticsSuShiE is a multiancestry fine-mapping method for molecular quantitative trait loci that leverages linkage disequilibrium heterogeneity to improve resolution, infer cross-ancestry effect size correlat...