Genomics and Rare Diseases

Long-read transcriptome analysis using IsoRanker for identifying pathogenic variants in Mendelian conditions

IsoRanker uses long-read transcriptomics to prioritize non-coding variants in Mendelian conditions by detecting expression outliers, allelic imbalance, and NMD, leading to the identification of pathogenic variants in one individual.

Patient-to-patient phenotype matching enables rare disease gene prioritization beyond curated gene-phenotype associations

This paper introduces SimPheny, a framework that uses patient-to-patient phenotype matching to prioritize genes for rare disease diagnosis, outperforming existing methods in cases with limited phenotype associations.

Gene identity, not variant effect, dominates ClinVar benchmarks of missense pathogenicity predictors

The paper evaluates missense pathogenicity predictors using ClinVar data, finding that gene identity, not variant effect, largely drives benchmark performance.

Multiplexed Quantification of Variant Abundance in the Globin Gene Family: Integrating Saturation Mutagenesis with Cross-Paralog Prediction

The paper presents a hybrid experimental and computational framework to quantify variant abundance in globin genes, using saturation mutagenesis and deep learning for cross-paralog prediction.

Ancestry-stratified variant classification in monogenic diabetes genes: annotation coverage and differential curation burden

The paper evaluates variant classification disparities in monogenic diabetes genes across ancestry groups using ClinVar and gnomAD, finding significant annotation gaps and curation biases in non-European populations.

OncoGenRAG: Evidence-Grounded Retrieval and BioBERT Classification for Precision Oncology Variant Interpretation

OncoGenRAG improves variant interpretation in oncology by combining retrieval and classification with a curated knowledge base, achieving high accuracy and reducing hallucinations.

Dynamics-aware Evolutionary Profiling Uncouples Structural Rigidity from Functional Motion to Enable Enhanced Variant Interpretation

This paper introduces Dynamics-Aware Evolutionary Profiling to separate structural rigidity from functional motion in proteins, improving variant interpretation by identifying dynamic-conserved residues.

Mapping pathogenic patterns in membrane transporters from the GLUT transporter family

The paper maps pathogenicity patterns in GLUT transporters by analyzing missense mutations and their structural impact across the family.

SVlog: a logic programming framework for understanding structural variation in genomic disease

SVlog provides a logic programming framework for analyzing structural variants in genomic disease by applying deterministic rules to genomic data and annotations.

Inferring Protein Variant Impacts Across Contexts

The paper evaluates imputation methods for contextual variant effects in MAVE studies, finding that method choice depends on data density and task requirements.

Context-dependent variant interpretation from Mendelian disease to genetic predisposition: a proof-of-concept using LPL

This paper proposes a context-dependent framework for variant interpretation by analyzing LPL loss-of-function variants, showing how residual activity levels influence clinical outcomes.

INDELVAR: structure-informed prediction of in-frame indel pathogenicity with calibrated PP3/BP4 thresholds

INDELVAR predicts pathogenicity of in-frame indels using structural and evolutionary features, achieving high AUROC scores and calibrated thresholds for both deletion and insertion types.

A Semantic + Neuronal Approach to Predict Pathogenic Variants in DNA Sequences

The paper presents a machine learning model that predicts pathogenic DNA variants using a semantic approach combined with CRF and BiLSTM, achieving state-of-the-art performance.

Shared inheritance reveals landscape of somatic and germline cancer risk in TP53

The paper distinguishes germline and somatic TP53 variants using whole-exome data from UK Biobank participants, showing somatic variants dominate cancer risk in middle-aged adults.

A structure and function-based complete mutational map of Human Hemoglobin using AI

The paper develops a pathogenicity prediction model for hemoglobin variants using structure-informed features and ML, showing strong performance compared to AlphaMissense and providing a complete mutational landscape for HbA.

Analysis of spliceosome-related coding and noncoding genes and pseudogenes reveals novel candidates

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

DAVE: how to use explainable AI to interpret missense variants for genome diagnostics based on functional protein modeling

DAVE uses explainable AI to interpret missense variants by integrating biophysically grounded features, improving variant classification and interpretability for genome diagnostics.

nf-cavalier: A Nextflow Pipeline for Rare Disease Variant Prioritization and Reporting

nf-cavalier automates variant annotation, filtering, and reporting for rare Mendelian diseases using customizable criteria and generates user-friendly outputs for clinical teams.

fastVEP: A Fast, Comprehensive Variant Effect Predictor Written in Rust

fastVEP is a fast, comprehensive variant effect predictor implemented in Rust, outperforming the Perl-based Ensembl VEP in speed while maintaining accuracy.

Assessing Computational Models for Pharmacogenomic Variant Interpretation

This study evaluates computational models for predicting pharmacogenomic variant effects, finding that StructureDCA outperforms other methods in distinguishing functional variants.

Detecting pathogenic structural variation in families with undiagnosed rare disease in a national genome project

This study uses long-read sequencing to identify pathogenic structural variants in undiagnosed rare disease families, increasing diagnostic yield in three families.

Guidance for clinical variant classification in genes for spliceosomal small nuclear RNAs

The paper provides guidance for classifying variants in snRNA genes and introduces RNUdb, a tool to support variant annotation and classification.

Challenges in Classification of PKD1 Missense Variation in Autosomal Dominant Polycystic Kidney Disease

The paper evaluates the performance of in silico tools in classifying PKD1 missense variants as pathogenic or benign, finding most are classified as VUS and tools lack reliability.

ClinGen Glaucoma Variant Curation Expert Panel recommendations enhance classification of myocilin variants

The paper curates 271 MYOC variants in open-angle glaucoma patients using updated ClinGen guidelines, increasing definitive classifications and highlighting the need for functional evidence.

Variant characterization in the intrinsically disordered human proteome

The paper improves variant effect prediction in intrinsically disordered regions by combining sequence analysis, AlphaFold, and experiments to annotate protein interactions and predict deleterious variants.

Sequence effects on mutation frequencies investigated in whole-genome sequenced UK Biobank participants

The paper analyzes mutation frequencies in UK Biobank whole-genome sequences, finding that AC25 variants closely match de novo mutations and are influenced by DNA context and transcriptional processes.

MetaSplice: pathogenicity prediction and ACMG/AMP evidence for intronic variants outside the canonical splice sites

MetaSplice improves pathogenicity prediction for non-canonical intronic variants by combining splicing predictions with conservation and gene-level constraints, achieving higher accuracy than existing tools.

Enhancing Missense Variant Classification in Predicted Intrinsically Disordered Regions

The paper enhances missense variant classification in intrinsically disordered regions by integrating IDR-specific features with existing predictors, significantly improving PR-AUC scores.

Comprehensive Mapping of SGCA Variant Effects Reveals Domain-Specific Constraints Relevant to Sarcoglycanopathies

The paper systematically evaluates SGCA variant effects using saturation mutagenesis to distinguish functional and non-functional variants, revealing domain-specific constraints in sarcoglycanopathies.

An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers

The paper benchmarks missense pathogenicity predictors on cancer drivers and provides a per-gene calibration map to improve their performance in somatic variant interpretation.