Samuel A. Lambert

This study identifies DNA binding motifs for 98 human transcription factors using meSMiLE-seq, revealing methylation-sensitive binding preferences for some TFs.

The paper uses GHT-SELEX to show many human TFs have high intrinsic sequence specificity and complex DNA binding, often matching in vivo ChIP-seq results.

OmicsPred collects 3,339,469 genetic prediction models for transcript, protein and metabolite traits with harmonised metadata and MetaXcan/PGSC-Calculator files, plus multi-ancestry Million Veterans Program phenome-wide association results.

This study identifies genetic determinants of plasma protein variance across ancestries and shows their impact on cardiometabolic disease risk.

The paper evaluates cross-platform DNA motif discovery tools using 4,237 experiments to identify reliable transcription factor binding motifs and highlights challenges in motif detection.

This study identifies genetic loci influencing variance in blood cell traits and shows that incorporating variance polygenic scores improves prediction accuracy.

This study identifies metabolic reaction fluxes that interact with CAD risk alleles, revealing their role as amplifiers or buffers in disease susceptibility.

This study identifies genetic determinants of blood gene expression and splicing, linking them to molecular phenotypes and health outcomes through QTL analysis and colocalization.

The paper systematically determines the sequence specificity of 332 poorly characterized human transcription factors, identifying over 4,000 experiments and revealing tens of thousands of new TF binding sites.

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.

The paper introduces new features and tools for the PGS Catalog to enhance FAIR research, enabling reproducible and equitable polygenic score calculations.

The paper develops genetic scores for 17,227 molecular traits using multi-omic data from INTERVAL and validates them across ancestries, demonstrating their utility in pathway analysis and disease association discovery.

The paper develops genetically personalised organ-specific metabolic models to identify associations between metabolic fluxes and disease risk, finding 97 fluxes linked to coronary artery disease.

This study assesses the transferability of genetic loci and polygenic scores for cardiometabolic traits from European-ancestry samples to British Pakistanis and Bangladeshis, finding high transferability for most loci but variable performance for polygenic scores.

The paper defines a standard format for GWAS summary statistics to improve data sharing and analysis.

The paper uses polygenic scores to identify plasma proteins causally linked to cardiometabolic diseases and finds some are targets for existing therapies.

PGS Catalog standardizes 192 curated polygenic scores and metadata (86 traits); reapplied in UK Biobank, eight of nine colorectal cancer scores predicted disease in European-ancestry participants.

ClinGen and the PGS Catalog expand the GRIPS guideline into a 22-item Polygenic Risk Score Reporting Statement covering study populations, model construction, evaluation, and clinical interpretation.