whole-exome sequencing

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

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.

The paper identifies six patients with biallelic IRAK4 variants causing severe neurological autoinflammation without immunodeficiency, expanding the known phenotype of IRAK4-related disease.

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.

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.

The paper predicts NAT2 genotypes and phenotypes in African populations using bioinformatic tools and next-generation sequencing data to inform pharmacogenetic treatment strategies for tuberculosis.

This study evaluates methods to correct cytosine deamination artifacts in FFPE sequencing, finding enzymatic repair is most effective and FFPErase is the best computational method.

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 evaluates ddPCR as a primary diagnostic tool for vascular anomalies, finding it detects 51% of pathogenic variants in a cohort, with an overall diagnostic yield of 75% when combined with NGS.

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.

This paper presents a scalable workflow for producing high-purity circular single-stranded DNA using an M13 phagemid system, achieving yields of 120-195 µg from 300 mL culture.

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.

STR-PG provides a scalable framework for short-read STR genotyping by decoupling locus representation from allele content, reducing computational costs while maintaining accuracy.

The paper identifies a de novo MFN2 mutation linked to dilated cardiomyopathy through functional and structural analysis.

The paper creates a database of ACE variants linked to Alzheimer's disease, estimates their population frequency, and links them to reduced blood ACE levels.

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

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

SIEVE is a deep-learning framework for variant and gene prioritization in exome studies, achieving strong discrimination and recovering known associations across diseases.

The paper characterizes the genetic landscape of Parkinson's disease in a Chilean cohort, identifying common pathogenic variants in LRRK2 and GBA1.

This study identifies a ubiquitous neoantigen-reactive T-cell response across multiple metastatic sites in a patient with pancreatic neuroendocrine tumor, supporting the use of mutation-sharing status for neoantigen selection in immunotherapy.

The paper reports a patient with a neurodevelopmental disorder caused by biallelic EXOSC6 variants, expanding the known spectrum of exosomopathies.

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.

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

The paper identifies increased GPCR pathway activity in breast cancer ovarian metastases and links it to migration and F-actin reorganization through CaSR.

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

EXCAVATE-HT identifies targetable genomic variants for allele-specific CRISPR editing by analyzing population data and generating gRNA libraries.

CESAR improves CNV detection in low-tumor fraction ctDNA by recalibrating depth ratios using anchor selection and segmentation, outperforming CNVkit in sensitivity and reproducibility.

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.