Moriel Singer‐Berk

The paper evaluates incomplete penetrance in 4,325 rare disease families, finding 1.6% of diagnosed cases involve inherited variants from unaffected parents and showing divergent transcriptional effects in CHD8-related cases.

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.

The paper identifies novel spliceosome-related genes and pseudogenes associated with rare diseases using variant analysis and prioritization methods.

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.

This paper estimates the global prevalence of GSD IV and APBD by analyzing GBE1 variants across nine genetic groups, finding 1 in 235,784 individuals are affected.

The paper estimates genetic prevalence for 22 autosomal recessive conditions using gnomAD data and develops a tool to democratize these calculations, highlighting the dynamic nature of prevalence estimates.

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 estimates the genetic prevalence of PLA2G6-associated neurodegeneration using database and literature-based approaches, finding higher prevalence in African/African-American and Asian populations.

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.

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 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 SMC3 loss-of-function variants associated with variable growth and developmental features, including some unexpected phenotypes like bone marrow failure and leukemia.

This paper presents a framework to reduce false positives in predicted loss-of-function variants by analyzing LoF evasion mechanisms and adjusting ACMG/AMP guidelines.

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.

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.

The paper uses primate genetic data to predict human variant pathogenicity with a deep learning classifier trained on 4.3 million common missense variants.

This paper provides recommendations for interpreting non-coding variants in clinical settings, adapting existing guidelines to account for their role in disease.

The paper evaluates penetrance and variable expressivity of monogenic metabolic conditions using exome data from 77,184 individuals, finding that monogenic variants have larger effect sizes than polygenic scores but low penetrance.

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.