Genomics and Rare Diseases

Variant scoring performance across selection regimes depends on variant-to-gene and gene-to-disease components

This study evaluates variant scoring methods across different selection regimes, showing their performance depends on variant-to-gene and gene-to-disease factors.

Variant classification guidelines for animals to objectively evaluate genetic variant pathogenicity

This paper develops and validates variant classification guidelines for animals, improving the accuracy of pathogenicity assessment in cats and eight other species.

Expanding the Russian allele frequency reference via cross-laboratory data integration: insights from 7,452 exome samples

The paper integrates exome data from 7,452 Russian samples to create a population-specific allele frequency reference, identifying rare variants and clusters within the Russian population.

altAFplotter: a web app for reliable UPD detection in NGS diagnostics

altAFplotter detects uniparental disomies in NGS data by analyzing runs of homozygosity and variant inheritance ratios, providing a web tool for reliable UPD analysis.

Deep mutational scanning of the human insulin receptor ectodomain to inform precision therapy for insulin resistance

The paper uses deep mutational scanning to assess the functional impact of INSR variants, identifying clinically relevant function scores and potential gain-of-function variants.

Assigning credit where it's due: An information content score to capture the clinical value of Multiplexed Assays of Variant Effect

The paper introduces an information content score to quantify the clinical value of MAVEs, showing it captures more information than just reclassifying variants.

The PS4-Likelihood Ratio Calculator: Flexible allocation of evidence weighting for case-control data in variant classification

The paper introduces PS4-LRCalc, a tool that quantitatively assigns evidence for variant classification using case-control data, enabling continuous scoring instead of dichotomous PS4 scoring.

One-Sided Matching Portal (OSMP): a tool to facilitate rare disease patient matchmaking

The paper introduces OSMP, a tool for one-sided genomic matchmaking in rare disease patients, which efficiently filters variant occurrences to prioritize clinically relevant matches.

Variant Graph Craft (VGC): A Comprehensive Tool for Analyzing Genetic Variation and Identifying Disease-Causing Variants.

VGC is a VCF file visualization and analysis tool that provides variant data extraction, visualization, and integration with external databases for gene function and variant interpretation.

Substantial role of rare inherited variation in individuals with developmental disorders

The paper investigates the role of rare inherited coding variants in developmental disorders by analyzing family and case/control data, finding significant burdens of damaging variants and estimating their population attributable risk.

Proteome-scale prediction of molecular mechanisms underlying dominant genetic diseases

The paper introduces a statistical model to predict dominant-negative, gain-of-function, and loss-of-function mechanisms of protein-altering mutations in human genes and validates its performance on unseen data.

Genomic and biological panoramas of non-muscle actinopathies

The paper analyzes clinical and mechanistic data from individuals with ACTB/ACTG1 variants to identify distinct disease phenotypes and molecular mechanisms of non-muscle actinopathies.

Untargeted proteomics enables ultra-rapid variant prioritization in mitochondrial and other rare diseases

This study uses untargeted proteomics to rapidly prioritize genetic variants in mitochondrial and other rare diseases, achieving functional evidence for 83% of cases in a cohort.

Genotypic and phenotypic analysis of 173 patients with extremely rare pathogenic mutations who applied for experimental antisense oligonucleotide treatment

The paper analyzes genotypic and phenotypic data from 173 patients with nano-rare mutations to explore genotype-phenotype relationships and the potential for antisense oligonucleotide therapy.

Assessment of ability of AlphaMissense to identify variants affecting susceptibility to common disease

This study evaluates AlphaMissense's ability to identify variants affecting disease susceptibility across 18 genes, comparing it to 43 other annotation methods.

Unveiling the Landscape of Reportable Genetic Secondary Findings in the Spanish Population: A Comprehensive Analysis Using the Collaborative Spanish Variant Server Database

The paper analyzes genetic secondary findings in the Spanish population using the Collaborative Spanish Variant Server database, finding 5% of individuals have reportable variants in 32 ACMG-listed genes.

Assessment of the evidence yield for the calibrated PP3/BP4 computational recommendations

The paper assesses rare missense variants in genome sequences using PP3/BP4 evidence strength classifications and finds few variants meet strong or moderate criteria.

Genetic Transformer: An Innovative Large Language Model Driven Approach for Rapid and Accurate Identification of Causative Variants in Rare Genetic Diseases

This paper introduces Genetic Transformer (GeneT), an LLM-driven method that significantly reduces candidate variant numbers and improves recall in rare disease diagnosis.

PROTEORIZER: A holistic approach to untangle functional consequences of variants of unknown significance.

Proteorizer contextualizes variants of unknown significance by integrating functional knowledge from related proteins and their 3D structures to predict functional consequences.

TRGT-denovo: accurate detection of de novo tandem repeat mutations

TRGT-denovo accurately detects de novo tandem repeat mutations in family trios, reducing false positives and improving precision compared to genotype-based methods.

Stratifying variant deleteriousness and trait-modulating effect under human recent adaptation

This study introduces a deep learning framework, FIND, to better classify genetic variants by their deleteriousness and trait-modulating effects, showing improved performance over existing methods.

Functionally constrained human proteins are less prone to disruption of stability caused by single amino acid substitutions

The paper quantifies how functionally constrained human proteins are less affected by stability-disrupting missense mutations and shows their depletion of extreme stability-changing variants in disease-free populations.

A New Era in Missense Variant Analysis: Statistical Insights and the Introduction of VAMPP-Score for Pathogenicity Assessment

This paper evaluates 52 in silico pathogenicity predictors (ISPPs) for missense variants and introduces VAMPP-score, a statistical framework that improves variant classification by integrating the best-performing predictors.

Bayesian estimation of gene constraint from an evolutionary model with gene features

This paper introduces a Bayesian framework combining population genetics and machine learning to estimate gene constraint, improving accuracy for short genes and providing a flexible tool for gene-level property estimation.

Saturation Genome Editing Resolves the Functional Spectrum of Pathogenic VHL Alleles

This study uses Saturation Genome Editing to functionally assess VHL variants, identifying pathogenic alleles and their mechanisms in cancer.

Empowering rare variant burden-based gene-trait association studies via optimized computational predictor choice

The paper evaluates computational predictors for rare variant burden tests and identifies two top predictors that enhance gene-trait association discovery in the UK Biobank.

Statistics to prioritize rare variants in family-based sequencing studies with disease subtypes

This paper develops methods to prioritize rare variants in family-based sequencing studies with disease subtypes by comparing global and local approaches for variant prioritization.

Exploring the genetic and epigenetic underpinnings of early-onset cancers: Variant prioritization for long read whole genome sequencing from family cancer pedigrees

This study uses long-read whole genome sequencing from family cancer pedigrees to prioritize genetic variants in early-onset cancers, identifying potential disease-causing mutations.

A unified meta-regression model identifies genes associated with epilepsy

The paper presents a unified meta-regression model that identifies epilepsy-associated genes by integrating constraint predictions, pathogenicity scores, and variant annotations from multiple datasets.

Considerations for reporting variants in novel candidate genes identified during clinical genomic testing

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