Namrata Gupta

The paper reports on the All of Us multi-omics cohort, identifying 182,246 QTLs and demonstrating rare variant effects across proteomic and transcriptomic data.

Himito is a graph-based toolkit for analyzing mitochondrial genomes using long reads, achieving superior performance in assembly and variant calling and revealing age-related patterns in the All of Us dataset.

The paper analyzes expression and splicing quantitative trait loci (e/sQTL) across multiple tissues in the TOPMed dataset and finds that secondary e/sQTL signals are still discoverable, with many GWAS signals colocalizing with these e/sQTL.

This study identifies 44 genetic loci associated with pulmonary artery diameter across COPD and population-based cohorts, highlighting shared causal variation between pulmonary and systemic vascular biology.

The paper performs large-scale GWAS and RVAS on 392,030 whole genomes from All of Us, identifying 49,863 associations and 193 novel pLoF gene-phenotype links through meta-analysis with UK Biobank.

The paper performs whole exome sequencing on 44,028 British South Asians to identify gene-phenotype associations and knockout genes, finding novel links and implications for drug development.

The paper integrates genomics and transcriptomics data from human heart samples to identify regulatory mechanisms linking genetic variation to dilated cardiomyopathy.

The paper analyzes long-read sequencing data from the All of Us Research Program to identify structural variants and their associations with diseases in a large cohort of Black or African American participants.

This study uses whole-genome sequence data from diverse participants to identify novel genetic loci associated with brain structural volumes, highlighting the importance of diverse cohorts in uncovering genetic architecture.

The paper identifies CR1 variants as a risk factor for FSGS across diverse populations through a case-control study and variant analysis.

The paper conducts proteome-wide and transcriptome-wide association studies for blood lipids, finding high-level consistency between proteome and transcriptome-lipid associations across tissues.

The paper identifies a common flanking variant linked to increased meiotic stability at the FGF14-SCA27B repeat locus.

The paper maps interaction QTLs (iQTLs) for cell type, age, and other variables in blood multi-omic data to identify context-specific genetic regulatory effects.

Rare-variant depletion in 1kb windows of 76,156 gnomAD genomes, versus feature-adjusted mutation expectations, marks regulatory elements and outperforms seven alternative scores at flagging functional non-coding variants.

The paper develops a method to infer compound heterozygosity from exome sequencing data, achieving high accuracy in phasing rare variants for recessive disease diagnosis.

The paper identifies impactful rare variants by integrating multi-omic data from MESA, showing that combining expression and protein data increases the detection of rare stop and frameshift variants.

This paper introduces MCFA, an unsupervised integration method for multi-omic data, and applies it to five omics types across 614 samples to infer shared and private factors.

This study performs a multi-ancestry GWAS on lung function and COPD, identifying 559 genes and 29 pathways, and showing genetic risk scores are associated with COPD across ancestries.

The paper shows that variant effect sizes on quantitative endophenotypes support pathogenicity in monogenic disease genes.

The paper performs single-variant and gene-based association analyses of 4,529 phenotypes using exome data from 426,370 UK Biobank individuals, finding associations linked to variant frequency and deleteriousness.

This study investigates how rare and common genetic variations contribute to QT interval duration, finding that both monogenic and polygenic factors influence QTc prolongation, with polygenic risk modulating the effect of rare variants.

The paper describes AnVIL, a cloud-based platform that enables genomic data analysis without data transfer, improving security, scalability, and collaboration.

This study identifies 35 genes associated with circulating lipid levels using rare coding variants from 170,000 exomes across multiple ancestries.

The paper introduces Giraffe, a pangenome mapper that improves genotyping of SNVs, indels, and SVs in 5,202 human genomes using the vg toolkit.

The paper analyzes gene expression in African American and Latino children to show ancestry-specific genetic architecture and highlights the benefits of diverse genomic studies.

This study investigates the impact of heterozygous ABCG5 LoF variants on LDL-C levels and CAD risk, finding a significant association with elevated LDL-C and doubled CAD risk.

The paper evaluates potential drug targets using loss-of-function genetic variants from gnomAD, highlighting the importance of deep curation and targeted recall studies for drug discovery.

From 125,748 exomes and 15,708 genomes, 443,769 high-confidence predicted loss-of-function variants yield LOEUF, a continuous gene intolerance score tracking mouse lethality, cell essentiality, and disease associations.

The paper develops an expression-based annotation metric to improve rare variant interpretation by filtering false-positive loss-of-function variants and identifying pathogenic variants in highly expressed exons.

Short-read genome sequencing of 14,891 diverse genomes yields 433,371 structural variants (SVs) for gnomAD; loss-constrained genes also resist duplication, and clinical SV carrier rates are benchmarked.