whole-exome sequencing

An AI-assisted C++17 port of VarDictJava gives byte-identical calls on five exome samples while running 3.7-4.8 times faster on one core and needing 8-17 times less memory.

MetaDome now supports GRCh38 alongside GRCh37, adds coordinate lookup, and identifies 52,463 GRCh38 ClinVar missense variants of uncertain significance with uncontradicted pathogenic evidence at homologous Pfam-domain positions.

The paper identifies 55 individuals with pathogenic PTEN variants in a population-based cohort, revealing higher prevalence and broader clinical features of PHTS than previously recognized.

The paper evaluates computational frameworks to prioritize pathogenic variants in deafness-associated genes, identifying 28,866 VUSs with high pathogenicity probability and improving diagnoses for 12 patients.

This study examines genetic and immune heterogeneity in HCC, finding significant discordance in genetic and immune profiles between multifocal tumours.

GenePy computes gene-level burden scores using variant data to improve diagnostic strategies for rare diseases through automated, scalable workflows.

This study examines the genetic contributions to emotional and behavioural symptoms in childhood and adolescence using common and rare variants from two large cohorts.

This study combines Msh2 depletion and proofreading-deficient DNA polymerase ε expression to enhance mutagenesis, enabling identification of drug resistance mutations and cytotoxin mechanisms in SCLC cells.

This study identifies key oncogenic pathways and targetable genes in MEN1-wild-type low-grade pancreatic NETs that drive metastasis, offering a therapeutic strategy based on pathway intensity rather than mutation count.

The paper identifies an ERCC2 mutation-associated mutational signature in targeted panel sequencing data linked to nucleotide excision repair deficiency in bladder cancer and shows its clinical relevance.

The paper identifies recurrent copy-number alterations in RCC brain metastases and shows their association with poor prognosis and metastatic potential across multiple cancers.

T-Rex provides a standardized, no-programming-required tool for analyzing whole-exome sequencing trio data, achieving high precision and sensitivity in variant calling and filtering.

aiDIVA uses AI and LLMs to prioritize causal genetic variants in rare diseases, achieving high accuracy in identifying top candidates.

Genomize-SEQ is a web-based platform for genomic variant classification and prioritization, achieving high accuracy in identifying causative variants for rare diseases.

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.

This study expands CIRdb with whole-exome sequencing data from 920 Canary Islanders, identifying 387,555 variants, including 15.1% previously unreported and 74.4% rare.

This study identifies HER2 as a prognostic marker in GCA and suggests anti-inflammatory and immune checkpoint inhibition as therapeutic strategies for HER2-negative patients.

This paper introduces RareEffect, a method for estimating rare variant effects and improving polygenic risk prediction using UK Biobank whole exome sequencing data.

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.

The paper develops FunBurd to analyze gene dosage effects on 43 traits in UK-Biobank, finding pleiotropy and non-monotonic responses linked to genetic constraint and brain-specific mechanisms.

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

This study uses deep sequencing to identify genetic variants in focal cortical dysplasias, finding pathogenic variants in 71% of cases and highlighting the importance of somatic variants in FCDIIb.

The paper analyzes somatic mutation profiles in normal human tissues to identify mutagenic mechanisms and their association with age, disease, and environmental exposures.

clinTALL is a deep learning framework that classifies pediatric T-ALL subtypes and predicts treatment outcomes using multimodal data, achieving high accuracy and concordance indices.

The paper develops synth4bench, a synthetic data pipeline to benchmark tumor-only somatic variant callers, revealing inconsistencies in tool performance and highlighting the need for sequencing optimization and caller selection.

This study evaluates polygenic risk scores (PRS) for colorectal cancer (CRC) screening, showing they stratify risk independently of ancestry and sex but offer limited additional predictive value when combined with FIT.

DiagAI, a machine-learning system, improves variant interpretation in genetic testing by prioritizing causal variants, outperforming existing tools with higher diagnostic yield and shorter variant shortlists.

The paper demonstrates that integrating CNV detection into exome sequencing analysis improves diagnostic yield for developmental disorders in the DDD-Africa cohort by 8.3% without additional costs.

Homozygosity for hypomorphic IL23R variants (G149R, G300V, R381Q) partly impairs IL-23-dependent IFN-γ production in patient cells; with L372F (effect inferred), they are enriched in tuberculosis, not MSMD or CMC patients.

Abundance scores for 8,891 TSC2 missense variants, plus mTOR pathway activity scores for 391, were calibrated to ACMG/AMP evidence. They putatively reclassify 212 of 276 clinical-cohort missense VUS.