ArticleCommunications biology2022
FVC as an adaptive and accurate method for filtering variants from popular NGS analysis pipelines.
Article in Communications biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- MRDsteer: quality-aware AI-driven closed-loop optimization enhances ctDNA-based minimal residual disease detection.Briefings in bioinformatics · 2026Article
- Clinical decisions in clonal hematopoiesis: a contemporary review for clinicians.Haematologica · 2026Review
- ChoCallate: a computational pipeline for consensus germline variant calling in genomic sequencing data.PeerJ · 2026Article
- Autonomous Self-Evolving Research on Biomedical Data: The DREAM Paradigm.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- A novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics.Briefings in bioinformatics · 2025Article
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Authors and funding
7 authors.
Funding
Abstract
The quality control of variants from whole-genome sequencing data is vital in clinical diagnosis and human genetics research. However, current filtering methods (Frequency, Hard-Filter, VQSR, GARFIELD, and VEF) were developed to be utilized on particular variant callers and have certain limitations. Especially, the number of eliminated true variants far exceeds the number of removed false variants using these methods. Here, we present an adaptive method for quality control on genetic variants from different analysis pipelines, and validate it on the variants generated from four popular variant callers (GATK HaplotypeCaller, Mutect2, Varscan2, and DeepVariant). FVC consistently exhibited the best performance. It removed far more false variants than the current state-of-the-art filtering methods and recalled ~51-99% true variants filtered out by the other methods. Once trained, FVC can be conveniently integrated into a user-specific variant calling pipeline.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.