whole-exome sequencing

The paper identifies chromosome 20p11.2 deletions as a cause of congenital hyperinsulinism by disrupting FOXA2 expression in pancreatic beta-cells.

This study presents the first comprehensive mutational and transcriptional analysis of B-cell precursor lymphoblastic lymphoma (BCP-LBL), revealing molecular similarities to BCP-ALL but with distinct mutation patterns in epigenetic modifiers.

The paper introduces MuSE2.0, a tool that accelerates somatic mutation calling for whole-genome and whole-exome sequencing data from heterogeneous tumor samples, achieving significant speed improvements over existing methods.

This study conducts a multi-ancestry whole-exome sequencing analysis of alcohol use disorder in two cohorts, identifying genetic variants associated with AUD.

This study evaluates deep learning models for classifying pathogenic germline variants in hereditary breast cancer using UK Biobank data, finding limited clinical utility for variants of uncertain significance.

This study identifies biallelic CCN2 variants as the cause of autosomal recessive kyphomelic dysplasia through clinical, genetic, and zebrafish model analyses.

The paper introduces a cost-efficient sequencing method called Blended Genome Exome (BGE) that combines low-coverage whole genome and high-coverage exome data, achieving >99% concordance with 30x WGS for variant imputation and rare coding variant calling.

This study identifies rare protein-altering variants in TUBB4B and other genes associated with left-handedness using exome data from over 300,000 individuals.

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 uses machine learning to identify cancer driver mutations, finding that methods incorporating protein structure or functional genomic data outperform those using only evolutionary data, and validates their predictions using real-world patient cohorts.

This study identifies prognostic and predictive alterations in cutaneous melanoma using targeted DNA sequencing and clinical follow-up, finding NRAS mutations correlate with worse survival and elevated TMB with better progression-free survival on combination ICI.

The paper identifies a frequent PMS2CL pseudogene variant misclassified as a PMS2 variant in Brazilian patients, highlighting diagnostic challenges in genetic testing.

This study identifies a four-fold enrichment of treatable genetic disorders in psychiatric patients compared to the general population through targeted sequencing of 129 genes.

The paper compares pathogenicity features of missense variants in non-human livestock to human genomic data, finding higher odds of pathogenic classification in cross-species variants.

This study evaluates the clinical relevance of prostate cancer cell lines by comparing them to human patient data and multiomics profiles, finding they represent a small fraction of patients and recommending a tailored selection pipeline.

The paper detects neoantigen-reactive CD8+ T cells in tumor biopsies and peripheral blood post-checkpoint blockade therapy and identifies peptide hydrophobicity and treatment-induced phenotypes as factors influencing their response.

This study analyzes mitochondrial and Y-chromosome haplogroups in the Iranian population using whole-exome sequencing and SNP microarray data from 18,184 individuals, revealing patterns of genetic diversity and haplogroup distribution.

This study identifies a CLASP1 variant in a consanguineous family linked to lissencephaly, showing it disrupts microtubule interactions and contributes to brain development defects.

This study finds that universal exome sequencing in critically ill adults yields a 25% diagnostic rate and highlights race-based disparities in genetic diagnosis documentation.

This study uses cancer mutation data and machine learning to predict the pathogenicity of germline missense variants, showing strong performance in identifying disease-causing variants.

This study analyzes somatic mutational features in colorectal tumors from ancestrally diverse populations, finding ethnic and genetic ancestry associations with mutation patterns.

This study validates ZNF208 mutation (c.64G>A) as a specific biomarker for advanced phase CML through targeted resequencing in a case-control cohort.

This study identifies genetic variants associated with cerebral visual impairment (CVI) in two cohorts and highlights phenotypic associations with neurodevelopmental disorders.

This study identifies germline rare variants associated with clear and non-clear cell RCC, accounting for population stratification, and finds distinct risk patterns and somatic associations.

This study evaluates AlphaMissense's impact on gene-based testing for disease causation using UK Biobank exome data, finding no significant improvement in identifying disease-causing genes.

VaMP integrates neural networks and metabolic models to link genetic variants with cancer phenotypes, identifying significant genes and metabolic signatures across five cancer types.

The paper identifies a shared genetic risk module involving PSEN2 and actin regulation across alpha-synucleinopathies, linking them to Alzheimer's disease mechanisms.

vcfexpress is a high-performance tool for filtering and formatting VCF files using Lua expressions, offering speed and flexibility comparable to existing tools.

This study examines rare genetic variants in pediatric NAFLD patients with advanced fibrosis but finds no genome-wide significant associations with fibrosis or other histologic features.

The paper analyzes ZPR1 exome variants using computational methods to assess their pathogenicity and identifies ethnic differences in variant frequency.