Genomics and Rare Diseases

AFQuery: a bitmap-indexed, capture-aware allele frequency engine for clinical genomics cohorts

AFQuery computes capture-aware allele frequencies for clinical genomics cohorts, reducing errors and bias in variant classification.

MARRVEL-MCP enables natural language variant interpretation through autonomous workflow construction

MARRVEL-MCP enables natural language variant interpretation by allowing LLMs to autonomously construct workflows using curated genomic tools, improving performance over models without tool access.

Phenotype-Specific Recalibration of MAVE Data Enables Repurposing of BAP1 Functional Assays for Kury-Isidor Syndrome

The paper recalibrates BAP1 MAVE data for different disease phenotypes to enable accurate variant classification across related disorders.

A global survey of System Biology-based predictions of gene-rare disease associations to enhance new diagnoses

The paper predicts gene-rare disease associations using a network-based algorithm to improve variant prioritization and guide functional validation.

CharacTERT: A machine learning tool for classifying hTERT missense variants

CharacTERT classifies hTERT missense variants using machine learning models that integrate sequence and structure-based features, achieving high accuracy and sensitivity in predicting pathogenicity.

Multisite Evaluation of an Amplification-based Nanopore Sequencing Solution to Analyze Challenging Clinically Relevant Variants in Genes Associated with Hereditary Diseases

This study evaluates a nanopore sequencing workflow for detecting complex variants in hereditary disease genes across multiple labs, finding high agreement with standard methods.

From Text to Translation: Using Language Models to Prioritize Variants for Clinical Review

This paper introduces ClinVar-BERT, a model that prioritizes variants for clinical review by analyzing variant summaries and distinguishing functional evidence, achieving high accuracy in predicting loss of function.

AUTOMATED VERSUS MANUAL REANALYSIS IN RARE DISEASE GENOMICS

The paper compares automated and manual reanalysis of rare disease genome sequencing data, finding automated methods achieve similar results with less effort.

Building an Interoperable Rare Disease Multi-omic Resource: The GREGoR Data Model and Dataset

The paper introduces a data model and dataset for rare disease research, enabling interoperable multi-omic data integration across clinical sites.

Calibrated high-throughput electrophysiology enables clinical interpretation of CACNA1G missense variants

This paper develops a calibrated electrophysiological framework to classify CACNA1G missense variants, identifying two variants as likely pathogenic and others as benign.

Challenging mtDNA tRNA Variant Guidelines: Emphasizing Single-Cell Analysis through Four Novel Variants

This study reclassifies four novel mtDNA variants using single-cell NGS analysis, highlighting the need for functional evidence and standardized criteria in variant interpretation.

Integrating enriched case data from national laboratory testing with population-based case-control analyses: a novel statistical likelihood-ratio methodology for PS4 applied to 325,345 breast cancer cases and 671,006 controls

The paper combines enriched case data with population-based case-control analyses using a likelihood-ratio methodology to classify variants in breast cancer susceptibility genes.

Evo 2 Predicts Cardiomyopathy-Associated Variants and Elucidates Their Underlying Mechanisms

This paper evaluates Evo 2's ability to predict pathogenicity and mechanisms of cardiomyopathy variants, showing high accuracy and structural feature identification.

Not Forgotten: Patient Experiences with Genetic Variant Reclassifications

This study explores patient experiences with genetic variant reclassifications, finding that re-contact practices significantly impact trust and perceived value of genetic testing.

A genome-wide deletion map in 125,730 individuals for novel rare disease gene and variant discovery

The paper creates a genome-wide map of homozygous deletions in 125,730 individuals, identifying novel rare disease genes and variants.

Bio-BLIP: A Multimodal Architecture for Transferable Reasoning in Genomic Variant Interpretation

Bio-BLIP is a multimodal architecture that integrates DNA, genes, proteins, and text to improve variant interpretation without task-specific fine-tuning, achieving better performance in variant prioritization and target gene prediction.

mehari: high-performance, strict HGVS-first variant effect prediction

mehari predicts variant effects with a strict HGVS-first approach, achieving high speed and accuracy compared to existing tools.

Advancing precision medicine in the Cardiac Intensive Care Unit using universal whole-genome sequencing

This study evaluates a universal whole-genome sequencing protocol in a cardiac intensive care unit, finding that 19.4% of neonates with congenital heart defects had clinically relevant variants identified.

Analyzing the Performance of Deep Learning Splice Prediction Algorithms

This study compares deep learning splice prediction algorithms, finding open-source reimplementations match the original SpliceAI in performance while outperforming traditional methods.

MucOneUp: A Simulation Framework for MUC1-VNTR Variant Benchmarking

MucOneUp generates MUC1-VNTR reference sequences and simulated sequencing reads to benchmark variant calling tools across platforms.

Image-based, pooled phenotyping reveals multidimensional, disease-specific variant effects

The paper introduces VIS-seq, an image-based method to assess variant effects on cellular phenotypes, revealing multidimensional variant impacts across different diseases.

G-SPRI: A Structure-Centric Graph Model for Comprehensive Prediction of Cancer Driver Events from Missense Mutations

G-SPRI predicts cancer driver events from missense mutations by integrating structural and mutation-specific features using a graph model.

AVITI sequencing of a four-generation CEPH/Utah pedigree confirms low mutation rates at homopolymer loci despite their low sequence complexity

The paper uses AVITI sequencing to analyze homopolymer mutation rates in a CEPH/Utah pedigree, confirming lower mutation rates and no significant paternal age effect compared to other STRs.

AnnotateMissense: a genome-wide annotation and benchmarking framework for missense pathogenicity prediction

AnnotateMissense integrates and benchmarks missense variant pathogenicity predictors using genome-wide data, achieving high performance with XGBoost.

VUStruct: a compute pipeline for high throughput and personalized structural biology

VUStruct analyzes genetic variants of unknown significance by integrating 3D protein structure data and machine learning to improve clinical and research interpretation of rare genetic disorders.

Whole Genome Sequencing for the Diagnosis of Rare Disorders

This study evaluates the diagnostic yield of whole-genome sequencing in 8966 patients with suspected rare diseases, finding a 35.8% diagnostic rate and additional variant detection.

Multi-Platform Curation in the Development of ACMG/AMP Specifications for Von Hippel Lindau (VHL) Disease

The paper describes the development of variant classification specifications for the VHL gene using ACMG/AMP guidelines, resulting in updated evidence codes and improved classification consistency.

ClinGen Variant Curation Interface Workshops: Training Variant Scientists on an International Platform

The paper describes international workshops training variant scientists on the ClinGen Variant Curation Interface (VCI) and reports on its usage and costs.

Molecular dynamics simulations of intrinsically disordered protein regions enable biophysical interpretation of variant effect predictors

The paper develops MDmis, a method using molecular dynamics simulations of intrinsically disordered regions to predict variant pathogenicity, finding Long IDRs show stronger pathogenic effects than Short IDRs.

The GA4GH Categorical Variation Representation Specification: A Unified Computational Framework for Reasoning over Genomic Variant Categories

The paper introduces Cat-VRS, a framework for computable representation of genomic variant categories to improve data interoperability and clinical interpretation.