Grace E. VanNoy

The Rare Genomes Project provides remote genomic sequencing to rare disease families, achieving a 23.3% diagnostic solve rate and highlighting the role of research in overcoming clinical diagnostic barriers.

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.

The paper presents genetic and phenotypic data from 521 children with neurodevelopmental disorders in Kenya and South Africa, highlighting high genetic diagnosis rates linked to environmental risk factors.

STRchive provides a dynamic resource for interpreting TR variants at disease loci, showing most TR diseases affect children and pathogenic genotypes exist in gnomAD without known disease prevalence.

This study evaluates the diagnostic yield of long-read nanopore sequencing in rare disease detection, finding it covers more genes and detects additional variants compared to short-read sequencing.

Mostly de novo variants in an 18 bp constrained region of U4 snRNA gene RNU4-2 cause a syndromic neurodevelopmental disorder, estimated to explain 0.41% of cases.

The paper evaluates variant prioritization methods for rare disease diagnosis using data from the Rare Genomes Project, finding that top models identify causal variants in most solved families and uncover potential candidates in unsolved ones.

This study identifies biallelic HMGCS1 variants as a novel cause of rigid spine syndrome, showing hypomorphic effects through functional and clinical analyses.

The paper identifies a de novo TLK1 mutation linked to neurodevelopmental disorder and immunodeficiency, showing impaired kinase activity and altered cytokine responses.

This study evaluates genome sequencing's diagnostic yield in a cohort of undiagnosed rare disease patients, finding it solves 29.3% of cases with specific variant types not detectable by exome sequencing.

This paper describes the Rare Genomes Project's efforts to address inequities in rare disease genomics by diversifying enrollment and understanding barriers to access.

The paper presents phenotype and genetic analysis of 206 children with neurodevelopmental disorders from Kenya and South Africa, identifying pathogenic variants in 17% of South African and 38% of Kenyan cases.

seqr is a web-based tool for analyzing rare disease genomic data, enabling variant filtering, annotation, and collaboration, with over 10,000 families analyzed and 300 novel disease genes discovered.