whole-exome sequencing

The paper identifies NRAP as a gene associated with elderly hypertrophic cardiomyopathy using an Indian Wellderly exome dataset and functional analysis.

MAJIQ-CLIN improves the detection of Mendelian disease-causing variants from RNA-Seq by addressing splicing aberrations, showing better accuracy and efficiency than existing tools.

This study identifies molecular vulnerabilities in colorectal cancer by analyzing MSI and MSS tumors, revealing distinct signaling pathways and potential therapeutic targets.

This study compares four exome enrichment kits, finding high coverage and variant calling accuracy, with Nanodigmbio showing highest precision and Vazyme and Nanodigmbio comparable to Agilent and Roche.

This study shows that GBA1 variants increase Parkinson's disease risk, with severe variants having higher risk than risk variants, and polygenic scores further increase this risk.

This study examines how allogeneic stem cell transplant affects subclonal evolution in chronic lymphocytic leukemia, identifying cellular homogeneity as a biomarker for immune response.

This study identifies 27 genes associated with head and neck cancer risk through exome sequencing and finds significant interactions between DNA repair gene variants and cigarette smoking.

This study identifies compound heterozygosity in the TTN gene as a recessive risk factor for nonsyndromic cleft lip and palate in an Indian family.

The paper identifies rare genetic variants associated with birth weight, highlighting genes involved in adipose tissue regulation, placental function, and insulin-like growth factor signaling.

CLOVER integrates multi-omics data with whole-slide images to generate molecular-aware slide representations, outperforming existing methods in cancer subtype classification and biomarker prediction.

RNAsum integrates WGS and WTS data to improve cancer diagnostics by corroborating clinically relevant variants and supporting therapeutic decisions.

This study identifies local genetic adaptation to habitat in wild chimpanzees, particularly to pathogens like malaria, using newly generated exomes.

The paper introduces MORFEE, a tool to identify SNVs altering small ORFs in human transcripts, and presents MORFEEdb, a catalog of such variants, showing over 45% of UTR-SNVs can affect upORFs or dORFs.

The paper analyzes somatic mutations across tissues and individuals using exome sequencing data from GTEx donors, identifying 8,470 variants and providing insights into mutation rates and mechanisms.

The paper identifies 19 risk genes for Hirschsprung Disease, including 15 novel candidates, showing ultra-rare variants contribute significantly to disease risk and severity.

This study compares deep learning and machine learning for biomarker prediction in cancer genomes, finding DL performs better in cross-assay and data-sparse settings.

protPheMut predicts cancer and neurodevelopmental disorder phenotypes from missense variants using interpretable machine learning, achieving high accuracy in PI3K and PTEN mutation analysis.

DeepPROTECTNeo predicts immunogenic neoepitopes by integrating genomic data and TCR-epitope interactions, outperforming existing methods with high accuracy and interpretability.

The paper analyzes genomic data from a diverse cohort to highlight genetic diversity and disparities in disease prevalence linked to ancestry and environment.

This study evaluates TMB cutoffs for predicting immunotherapy outcomes across multiple cancer types and endpoints, finding replicable associations for specific cutoffs in melanoma, lung, and bladder cancers.

EpiMolBio is a user-friendly software for genetic variability analysis, offering tools for sequence processing, conservation, mutation detection, and specialized HIV/SARS-CoV-2 analysis.

This study identifies three novel germline variants associated with nasopharyngeal carcinoma risk and introduces a refined polygenic risk score linked to EBV infection.

This study compares genomic features of left- and right-sided colon cancers using real-world data, finding significant differences in mutation burdens and survival outcomes.

The paper introduces Limpute, an efficient algorithm for genotyping common variants from low-coverage sequencing data, achieving high imputation accuracy with faster runtime than GLIMPSE2.

The paper introduces OpenPedCan, a harmonized multi-omic dataset of pediatric cancer patients, providing integrated genomic, transcriptomic, and proteomic data for research and clinical applications.

The paper compares whole exome sequencing and single-cell DNA sequencing in AML to assess clonal heterogeneity and evolution, finding both methods have strengths and limitations in variant detection and clonal analysis.

BayesRVAT improves rare variant association testing by integrating multiple annotations, increasing power and detecting novel gene-disease associations in real data.

The paper validates the NovaSeq6000 RUO platform with automated library preparation for clinical-grade whole-exome sequencing, showing equivalence to the CE-IVD certified system.

The paper uses nanopore sequencing to accurately phase a heterozygous deletion in the IKBKG gene in an IP family, confirming its location and X-inactivation status.

MTGCL identifies cancer driver genes using multi-task graph contrastive learning, improving performance by integrating multi-omics data and unlabeled node information.