Expressive

rs10241634 - LINC03007 - MIR148A

Magnitude 2.2 · 3 studies on file

Reported associations

  • A scalable variational inference approach for increased mixed-model association power - Unknown journal (n.d.) · Unknown authors · PubMed 39789286

    ABSTRACT: The rapid growth of modern biobanks is creating new opportunities for large-scale genome-wide association studies (GWASs) and the analysis of complex traits. However, performing GWASs on millions of samples often leads to trade-offs between computational efficiency and statistical power, reducing the benefits of large-scale data collection efforts. We developed Quickdraws, a method that increases association power in quantitative and binary traits without sacrificing computational efficiency, leveraging a spike-and-slab prior on variant effects, stochastic variational inference and graphics processing unit acceleration. We applied Quickdraws to 79 quantitative and 50 binary traits in 405,088 UK Biobank samples, identifying 4.97% and 3.25% more associations than REGENIE and 22.71%

  • A Genomics England haplotype reference panel and imputation of UK Biobank - Unknown journal (n.d.) · Unknown authors · PubMed 39134668

    ABSTRACT: We built a reference panel with 342 million autosomal variants using 78,195 individuals from the Genomics England (GEL) dataset, achieving a phasing switch error rate of 0.18% for European samples and imputation quality of r2 = 0.75 for variants with minor allele frequencies as low as 2 × 10−4 in white British samples. The GEL-imputed UK Biobank genome-wide association analysis identified 70% of associations found by direct exome sequencing (P < 2.18 × 10−11), while extending testing of rare variants to the entire genome. Coding variants dominated the rare-variant genome-wide association results, implying less disruptive effects of rare non-coding variants. A Genomics England haplotype reference panel constructed using sequence data from 78,195 individuals

  • Unraveling the genetic links between stature and disease in East Asians: A multi-biobank genetic correlation and risk prediction study - Unknown journal (n.d.) · Unknown authors · PubMed 41824406

    ABSTRACT: Both genetic and environmental factors affect human stature, including overall height and familial short stature (FSS), and it is associated with various health outcomes. However, the study of genetic connections between stature and health conditions remains lacking in East Asian populations. Hence, we conducted parallel genome-wide association studies (GWAS) of body height and FSS in the Han Taiwanese population, aiming to elucidate the genetic influences of stature on health and facilitate the formulation of precision-health strategies. We analyzed large-scale GWAS data on adult height (120,301 Han Taiwanese) and FSS (FSS; 2,050 cases, 27,966 controls) to examine cross-trait genetic correlations across five East Asian biobanks, and applied phenome-wide association studies (PheW

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