fine-mapping

Characterizing substructure via mixture modeling in large-scale genetic summary statistics

Summix2 uses mixture modeling to estimate and adjust for substructure in genetic summary data, improving the robustness and equity of research using diverse datasets.

Investigating misclassification of type 1 diabetes in a population-based cohort of British Pakistanis and Bangladeshis using polygenic risk scores

This study estimates that ~6% of insulin-treated diabetic individuals with ambiguous features in British Pakistanis and Bangladeshis have T1D, highlighting the need for autoantibody and C-peptide testing.

Local genetic adaptation to habitat in wild chimpanzees

This study identifies local genetic adaptation to habitat in wild chimpanzees, particularly to pathogens like malaria, using newly generated exomes.

Refining fine-mapping: effect sizes and regional heritability

This paper improves fine-mapping by estimating effect sizes and regional heritability using FINEMAP, showing it captures more heritability than BOLT and provides better precision.

GEM-Finder: dissecting GWAS variants via long-range interacting cis-regulatory elements with differentiation-specific genes

GEM-Finder identifies disease-associated CREs by integrating transcriptomic, epigenomic, and chromatin interaction data during endothelial differentiation, revealing 7.6 times more associations than conventional methods.

Uncovering the genetic underpinnings for different psychiatric disorder combinations

This study uses CombGWAS to analyze genetic correlations between psychiatric disorder combinations and cardiovascular disease, identifying shared and unique genetic factors.

Fine-mapping causal tissues and genes at disease-associated loci

This paper introduces TGFM, a method for fine-mapping causal tissues and genes at disease-associated loci using GWAS and eQTL data, identifying 147 causal elements per disease with 11% as gene-tissue pairs.

Funmap: integrating high-dimensional functional annotations to improve fine-mapping

Funmap improves fine-mapping by integrating high-dimensional functional annotations, achieving better power and controlled false positive rates compared to existing methods.

Statistical examination of shared loci in neuropsychiatric diseases using genome-wide association study summary statistics

This study uses GWAS summary statistics to identify shared genetic loci across neuropsychiatric diseases and finds HLA region associations with potential shared causal variants.

An integrative analysis of consortium-based multi-omics QTL and genome-wide association study data uncovers new biomarkers for lung cancer

The paper integrates multi-omics QTL and GWAS data to identify 123 novel biomarkers for lung cancer and reveals cross-omics regulatory pathways.

SURFBAT: a surrogate family-based association test building on large imputation reference panels

SURFBAT approximates transmission-disequilibrium tests using imputed haplotypes to detect genotype-phenotype associations while being robust to population stratification.

Post-GWAS Prioritization of Genome-Phenome Associations in Sorghum

This study develops SSPA to prioritize SNPs associated with canopy height and growth rate in sorghum using GWAS and feature engineering.

Small-cohort GWAS discovery with AI over massive functional genomics knowledge graph

KGWAS improves GWAS power in small cohorts by integrating a functional knowledge graph, discovering more associations for rare diseases.

Fine-mapping SLE-MHC associations revealed independent contributions of HLA missense variants and C4 copy number variations

This study identifies independent genetic contributions of HLA missense variants and C4 copy number variations to SLE risk using a new East Asian MHC imputation panel.

Genome-wide association analysis reveals insights into the molecular aetiology underlying dilated cardiomyopathy

This study identifies 80 genetic loci and 61 effector genes associated with dilated cardiomyopathy through GWAS and integrates transcriptomic data to uncover biological pathways and cellular states involved in the disease.

Accounting for heterogeneity due to environmental sources in meta-analysis of genome-wide association studies

This paper introduces env-MR-MEGA, a meta-regression model that adjusts for environmental and ancestral heterogeneity in GWAS meta-analysis, improving association power.

Polygenic risk of idiopathic pulmonary fibrosis and COVID-19 severity

This study calculates polygenic risk scores for idiopathic pulmonary fibrosis (IPF) and finds they are associated with increased risk of severe COVID-19 outcomes, particularly in younger males.

Sparse matrix factorization robust to sample sharing across GWAS reveals interpretable genetic components

This paper introduces GLEANR, a method for sparse matrix factorization of GWAS summary statistics that accounts for sample sharing and identifies interpretable genetic factors.

A consensus variant-to-function score to functionally prioritize variants for disease

This paper introduces a consensus variant-to-function score to prioritize disease-causing variants, showing improved performance in heritability enrichment and fine-mapping.

ENCODE guided WGS analysis can identify trait associated regulatory regions driven by rare-variants

The paper uses ENCODE-derived regulatory elements to analyze rare variants in WGS data, identifying 1,987 significant associations across 100 traits with high replication rates.

Fine-scale genetic structure and rare variant frequencies

The paper highlights the importance of fine-scale population structure in genetic studies, showing that smaller cohorts with distinct structure have higher rare variant frequencies, aiding in new genetic variant discovery.

Sequence sensitivity of open chromatin reveals constrained regulatory elements underlying human traits

The paper introduces CAMBUS, a machine-learning framework to identify functionally important open chromatin regions by measuring sequence sensitivity, and finds these regions are enriched for evolutionary constraint and disease-related variants.

BTS: scalable Bayesian Tissue Score for prioritizing GWAS variants and their functional contexts across omics data

BTS identifies causal variants and their functional contexts using GWAS data and functional genomic annotations, showing improved efficiency and biological insights.

Accounting for genetic effect heterogeneity in fine-mapping and improving power to detect gene-environment interactions with SharePro

This paper improves power to detect gene-environment interactions by adapting SharePro to account for genetic effect heterogeneity in fine-mapping.

Robust fine-mapping in the presence of linkage disequilibrium mismatch

RSparsePro improves fine-mapping accuracy in the presence of LD mismatch by using a probabilistic graphical model and variational inference, outperforming SuSiE in simulations and real applications.

Probabilistic Fine-mapping of Putative Causal Genes

This paper introduces INTERFACE, a probabilistic fine-mapping method that improves the identification of causal genes by integrating colocalization and transcriptome-wide association evidence.

The NHGRI-EBI GWAS Catalog: standards for reusability, sustainability and diversity

The GWAS Catalog now holds 625,113 curated SNP-trait associations from 6,921 publications plus >85K summary statistics datasets, with a new GWAS-SSF submission standard and GRCh38 harmonisation.

Comprehensive identification of coronary artery disease-associated variants regulating vascular smooth muscle cell gene expression

This study identifies CAD-associated variants regulating vascular smooth muscle cell gene expression through functional assays and eQTL integration.

BEATRICE: Bayesian Fine-mapping from Summary Datausing Deep Variational Inference

BEATRICE identifies causal variants from GWAS summary data using a Bayesian framework, outperforming baselines in coverage and finding the APOEε2 allele in Alzheimer's disease.

A Southern African Map of Blood Regulatory Variation Enables GWAS Interpretation

This paper presents a blood regulatory variation map from Southern African populations, showing increased utility for interpreting African genetic studies.