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Genetic testing is becoming more and more accepted in the auxiliary diagnosis and treatment of tumors. Due to the different performance of the existing bioinformatics software and the different analysis results, the needs of clinical diagnosis and treatment cannot be met. To this end, we combined Bayesian classification model (BC) and fisher exact test (FET), and develop an efficient software DeteX to detect SNV and InDel mutations. It can detect the somatic mutations in tumor-normal paired samples as well as mutations in a single sample. Combination of Bayesian classification model (BC) and fisher exact test (FET). We detected SNVs and InDels in 11 TCGA glioma samples, 28 clinically targeted capture samples and 2 NCCL-EQA standard samples with DeteX, VarDict, Mutect, VarScan and GatkSNV. The results show that, among the three groups of samples, DeteX has higher sensitivity and precision whether it detects SNVs or InDels than other callers and the F1 value of DeteX is the highest. Especially in the detection of substitution and complex mutations, only DeteX can accurately detect these two kinds of mutations. In terms of single-sample mutation detection, DeteX is much more sensitive than the HaplotypeCaller program in Gatk. In addition, although DeteX has higher mutation detection capabilities, its running time is only .609 of VarDict, which is .704 and .343 longer than VarScan and MuTect, respectively. In this study, we developed DeteX to detect SNV and InDel mutations in single and paired samples. DeteX has high sensitivity and precision especially in the detection of substitution and complex mutations. In summary, DeteX from NGS data is a good SNV and InDel caller.
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http://dx.doi.org/10.3389/fgene.2022.1118183 | DOI Listing |
Mol Genet Genomics
September 2025
Human Phenome Institute, MOE Key Laboratory of Contemporary Anthropology, Zhangjiang Fudan International Innovation Center, Fudan University, 825 Zhangheng Road, Shanghai, 201203, China.
Accurate variant calling is essential for next-generation sequencing (NGS)-based diagnosis of rare diseases, yet most benchmarking studies have focused on standard cell lines or trio-based samples, with limited relevance to sporadic cases. Here, we systematically compared the performance of DeepVariant and GATK HaplotypeCaller in two Chinese cohorts of patients with sporadic epilepsy (EP) and autism spectrum disorder (ASD). DeepVariant exhibited higher precision and sensitivity in detecting single nucleotide variants (SNVs), while GATK showed a distinct advantage in identifying rare variants, which are often key to understanding the genetic basis of rare diseases.
View Article and Find Full Text PDFMod Pathol
September 2025
Department of Medicine, University of Padua, Italy; Veneto Institute of Oncology, IOV-IRCCS, Padua, Italy. Electronic address:
A subset of gastric cancers (GCs) is linked to Epstein-Barr virus (EBV) infection. This study aims to characterize the histopathological and molecular features of EBV-associated GCs (EBVaGCs), focusing on predictive biomarkers and genomic and transcriptomic analysis. A total of 35 primary EBVaGCs were considered.
View Article and Find Full Text PDFExpert Rev Anticancer Ther
August 2025
Department of Public Health, University Federico II of Naples, Naples, Italy.
Introduction: In the era of precision medicine, molecular biomarker testing is increasingly becoming the standard of care for Non-Small Cell Lung Cancer (NSCLC) patients. Tissue and liquid biopsy-based Next-Generation Sequencing (NGS) is now highly recommended.
Areas Covered: Different NGS platforms emerged as a cost-effective strategy to perform a massive and parallel sequencing performing higher technical sensitivity than old generation technologies in detecting low abundant alterations in challenging diagnostic samples.
JCO Clin Cancer Inform
August 2025
Biofidelity Ltd, Cambridge, United Kingdom.
Purpose: Aspyre Lung is a targeted biomarker panel of 114 genomic variants across 11 guideline-recommended genes with simultaneous DNA and RNA for non-small cell lung cancer (NSCLC). In this study, we developed a machine learning algorithm to interpret fluorescence data outputs from Aspyre Lung, enabling the assay to be applied to both plasma and tissue samples.
Materials And Methods: Data for model training and testing were generated from over 13,500 DNA and RNA contrived samples, with variants spiked in at a variant allele frequency (VAF) of 0.
Addict Biol
August 2025
Department of Psychiatry, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Alcohol use disorder is closely related to genetic and environmental factors. However, the contribution of coding variation to alcohol use disorder susceptibility remains poorly understood. We aimed to identify genetic mutations in alcohol use disorder by whole exon sequencing.
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