whole-exome sequencing

This study evaluates in silico variant prediction tools for cancer genes, finding gene-specific performance issues and recommending validation for individual genes.

The paper maps the functional effects of MUTYH variants using deep mutational scanning and DNA repair reporters, resolving variants of uncertain significance and identifying risk-associated mutations.

The study identifies germline genetic variants in 95 Panamanian colorectal cancer patients, finding 10% with pathogenic variants in MUTYH, CHEK2, and other genes, but no mutations in mismatch repair genes.

This study compares whole-genome sequencing (WGS) and whole-exome sequencing (WES) in a pediatric Albanian population, finding WGS more effective in diagnosing rare genetic disorders and identifying complex variants.

This study shows that trio exome sequencing is effective as a standalone first-tier test for prenatal diagnosis, offering higher diagnostic yield and clinical impact compared to traditional methods.

Parabricks accelerates genomic analysis using GPU acceleration, reducing processing time while maintaining accuracy across various sequencing modalities.

The paper identifies co-segregating RUBCN and KANK1 mutations in a UK ALS family, showing their association with disease and functional impact on cellular processes.

The paper identifies characteristics of TP53 variants with reduced penetrance using ClinVar data and a random forest model, finding they have intermediate function, higher frequency, and delayed disease onset.

The paper investigates the association between clonal hematopoiesis gene variants and premature coronary artery disease in South Asian Indians, finding high prevalence and specific gene variant associations.

This study identifies biallelic germline variants in MCM8 and MCM9 as linked to polyposis, gastric cancer, early-onset colorectal cancer, and hypogonadism, with MCM9 variants showing stronger associations.

The paper assesses an automated variant prioritisation strategy for genomic newborn screening in the Generation Study, finding that 3-5% of samples require manual review and <1% need confirmatory testing.

This study analyzes mutational and expression patterns of ZNF217, ZNF703, and ZNF750 in Kenyan breast cancer patients, finding distinct mutation burdens and expression upregulation in tumors.

The paper identifies variants in PRPF8 and related genes associated with CAKUT, showing their role in splicing and ciliogenesis through functional experiments.

The paper uses population biobank data to identify and calibrate evidence of variant pathogenicity for 41 genes, finding that 2.6% of participants have rare variants with moderate or stronger evidence of pathogenicity.

The paper identifies novel immunotherapeutic targets in multiple myeloma high-risk subgroups using genomic data integration and validation.

The paper provides an integrated genomic analysis of NF1-associated peripheral nerve sheath tumors using RNAseq and WES data from 73 and 114 samples, respectively, accessible via the NF Data Portal.

The paper identifies enriched coding variants in a French-Canadian founder population and explores their association with inflammatory bowel diseases.

This study identifies genetic changes in IDH-mutant gliomas that correlate with treatment response and tumor evolution using longitudinal genomic data from 206 patient samples.

This study identifies genetic alterations associated with recurrence and radiotherapy response in ductal carcinoma in situ using whole-exome sequencing and copy number analysis.

This study estimates the global prevalence and carrier frequency of primary carnitine deficiency using gnomAD data and ACMG guidelines.

This study shows that gut microbiota-mediated lipid accumulation, through midgut elongation, enables Drosophila to adapt to blue light toxicity over generations.

This study develops a 295-gene targeted sequencing panel and an AI model to identify disease-initiating and transformative biomarkers in multiple myeloma.

GAME provides a standardized framework for benchmarking genomics models across tasks, enabling consistent evaluation and community contributions.

This study examines the long-term effects of chemotherapy on normal blood cells by analyzing mutation burdens and cell population structure in treated individuals.

Mixture modeling of 239 phenotype features in 5,392 SPARK autistic children defines four replicable classes carrying distinct common and rare variant signatures and developmental gene-timing patterns.

The paper annotates de novo variants near GWAS loci for cleft lip with or without cleft palate, finding noncoding variants in enhancer regions associated with craniofacial development genes.

DeepGraphMut uses graph-based deep learning to predict cancer prognosis from somatic mutation data, identifying subtypes and achieving high survival prediction accuracy across 16 cancer types.

The paper introduces a customizable pipeline for exome-wide rare variant gene-trait associations, demonstrating its utility by replicating three studies and providing a standardized framework for similar analyses.

This study establishes patient-derived organoids (PDOs) for HNSCC drug response testing, integrating AI-driven histopathology and multi-omics analysis to create a scalable preclinical model.

The paper analyzes germline DNA repair gene variants in BRCA1 and BRCA2 families to assess the prevalence of damaging variants in DNA repair genes beyond established breast cancer predisposing genes.