ArticleBioinformatics (Oxford, England)2019
smCounter2: an accurate low-frequency variant caller for targeted sequencing data with unique molecular identifiers.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.
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67 citing papers in PubMed.
- PD-L1 targeting and subclonal immune escape mediated by PD-L1 mutations in metastatic colorectal cancer.Journal for immunotherapy of cancer · 2021Trial
- High-Throughput Drug Screening and Multi-Omic Analysis to Guide Individualized Treatment for Multiple Myeloma.JCO precision oncology · 2021Trial
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- Fetal Fraction Signatures: A Quality Control Tool to Detect Potentially Confounding Situations in NonInvasive Prenatal Diagnosis of Monogenic Conditions.Clinical genetics · 2026Article
- Functional footprints of homologous recombination deficiency in prostate cancer revealed by ctDNA fragmentation and transcription factor accessibility.British journal of cancer · 2026Article
- bronko: ultrafast, alignment-free detection of viral genome variation.bioRxiv : the preprint server for biology · 2026Article
- Benchmarking UMI clustering tools for accurate detection of low-frequency variants from deep sequencing.Scientific reports · 2025Article
- A set cover algorithm identifies minimal circulating tumour DNA sequencing targets for colorectal cancer detection.Scientific reports · 2025Article
- Evaluation of urinary cfDNA workflows for the molecular profiling of malignant disease.iScience · 2025Article
- Alignment-free unique molecular identifier clustering suppresses sequencing errors for accurate detection of low-frequency DNA variants.Briefings in bioinformatics · 2025Article
- Overcoming intra-tumoral heterogeneity for biomarker discovery in the high-grade serous ovarian cancer proteome.NPJ precision oncology · 2025Article
- A Proteogenomic View of Synchronous Endometrioid Endometrial and Ovarian Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025Article
- Development of PowerMag System II for Isolation of Circulating Tumor Cells with Improved Purity.Biomedicines · 2025Article
- Early Detection, Precision Treatment, Recurrence Monitoring: Liquid Biopsy Transforms Colorectal Cancer Therapy.Current cancer drug targets · 2025Review
- Evaluating Bioinformatics Processing of Somatic Variant Detection in cfDNA Using Targeted Sequencing with UMIs.International journal of molecular sciences · 2024Article
- Benchmarking UMI-aware and standard variant callers for low frequency ctDNA variant detection.BMC genomics · 2024Article
- A20 haploinsufficiency disturbs immune homeostasis and drives the transformation of lymphocytes with permissive antigen receptors.Science advances · 2024Article
- Cell-Free DNA in Plasma Reveals Genomic Similarity Between Biliary Tract Inflammatory Lesion and Biliary Tract Cancer.Phenomics (Cham, Switzerland) · 2024Article
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7 authors.
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Abstract
motivationLow-frequency DNA mutations are often confounded with technical artifacts from sample preparation and sequencing. With unique molecular identifiers (UMIs), most of the sequencing errors can be corrected. However, errors before UMI tagging, such as DNA polymerase errors during end repair and the first PCR cycle, cannot be corrected with single-strand UMIs and impose fundamental limits to UMI-based variant calling.
resultsWe developed smCounter2, a UMI-based variant caller for targeted sequencing data and an upgrade from the current version of smCounter. Compared to smCounter, smCounter2 features lower detection limit that decreases from 1 to 0.5%, better overall accuracy (particularly in non-coding regions), a consistent threshold that can be applied to both deep and shallow sequencing runs, and easier use via a Docker image and code for read pre-processing. We benchmarked smCounter2 against several state-of-the-art UMI-based variant calling methods using multiple datasets and demonstrated smCounter2's superior performance in detecting somatic variants. At the core of smCounter2 is a statistical test to determine whether the allele frequency of the putative variant is significantly above the background error rate, which was carefully modeled using an independent dataset. The improved accuracy in non-coding regions was mainly achieved using novel repetitive region filters that were specifically designed for UMI data. AVAILABILITY AND IMPLEMENTATION: The entire pipeline is available at https://github.com/qiaseq/qiaseq-dna under MIT license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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