Kiran V. Garimella

The paper analyzes genetic variation, ancestry, and DNA methylation in Hispanic/Latino participants using long-read sequencing, identifying novel variants and phenotype associations.

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 constructs a high-resolution human pangenome structural variant resource, identifies disease-associated SVs, and demonstrates its utility in filtering variants from probands and associating SVs with traits in a large cohort.

This study evaluates the diagnostic yield of short-read and long-read sequencing in rare diseases, finding limited added value from long-read sequencing despite increased variant discovery.

This paper develops computational tools for allelic imbalance analysis using single-nucleus RNA-seq and demonstrates their application in a Parkinson's disease cohort.

The paper analyzes over 800,000 human genomes to assess penetrance of clinically relevant variants, finding that 95% of pLoF variants in severe diseases have explanations for lack of disease manifestation.

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.

The paper uses long-read sequencing data to analyze STR variability across 2,645 individuals, identifying disease-associated STR loci with elevated allelic variability and introducing the PLVI metric.

POASTA is an optimal algorithm for partial order alignment that improves speed and memory efficiency, enabling larger alignments in bacterial gene datasets.

This paper resolves ring chromosomes, Robertsonian translocations, and complex structural variants using long-read sequencing and telomere-to-telomere assembly, revealing breakpoint structures and methylation changes.

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

The paper develops criteria for identifying, sharing, and reporting novel candidate genes in clinical genomic testing to improve diagnostic yield for Mendelian conditions.

The paper detects and classifies copy number variants in exome data from 6,633 families, identifying causal CNVs in 173 families and improving classification standards.

The paper identifies a novel neurodevelopmental disorder caused by de novo deletion of the lncRNA CHASERR, showing its role in regulating CHD2 expression and causing developmental and epileptic encephalopathy.

The paper compares short-read and long-read sequencing in the All of Us initiative, finding HiFi reads provide the most accurate variant calling and presents a cloud-based pipeline for long-read analysis.

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.

This study compares variant calling precision and recall of Oxford Nanopore and PacBio HiFi platforms across different sequence coverages.

This paper introduces MAS-ISO-seq, a method to boost throughput of long-read RNA sequencing for isoform discovery, showing improved detection of differentially spliced genes and cell clustering in T cells.

This paper presents a high-quality, chromosome-level genome assembly of the brown bear, improving upon previous assemblies and enabling better analysis of evolutionary and medical traits.

The paper uses long-read RNA-seq data to identify new transcripts and develop a tool to analyze genetic effects on transcript structure, revealing insights into splicing regulation and variant interpretation.

This paper introduces a deep learning framework called Cue for structural variant discovery and genotyping, showing improved performance over existing methods on synthetic and real data.

The paper presents a pipeline to call mitochondrial DNA variants in gnomAD, reporting population frequencies for 10,850 unique mtDNA variants across 56,434 individuals.

The paper describes the role of the Centers for Mendelian Genomics in advancing gene discovery through data sharing, collaboration, and resource development over the past decade.

The paper introduces Corticall, a graph-based method to detect de novo mutations using short-read and long-read data, validated on Plasmodium falciparum crosses.

The paper introduces a new data structure called the Linked de Bruijn Graph (LdBG) that integrates long-range connectivity information into de Bruijn graphs, improving performance in genome assembly and variant calling.