Evidence map›Paper›PMID 42859656›Full record

ArticleHuman mutation2026

VarSim: A Python Toolkit for HGVS Variant Description Validation, Normalization, and Representation Conversion.

Liu Sun, Rongshu Wang, Jian Yang

Abstract read
In one paragraph

Article in Human mutation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Liu SunDepartment of Computer Science School of Engineering Yuxi Normal University Yuxi China yxnu.net.ORCID https://orcid.org/0000-0002-1459-9478
Rongshu WangDepartment of Computer Science School of Engineering Yuxi Normal University Yuxi China yxnu.net.ORCID https://orcid.org/0000-0001-6585-7046
Jian YangDepartment of Computer Science School of Engineering Yuxi Normal University Yuxi China yxnu.net.ORCID https://orcid.org/0000-0003-2604-5824

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate and reproducible representation of genetic variants is essential for clinical genomics, variant databases, and genomic research. The Human Genome Variation Society (HGVS) recommendations provide a standardized framework for describing sequence variants, but practical HGVS processing commonly involves multiple interdependent tasks, including parsing, validation, normalization, coordinate transformation, protein consequence inference, and conversion between variant representation formats. We developed VarSim, a lightweight Python toolkit that integrates these operations within a reference-aware workflow based on version-pinned Matched Annotation from NCBI and EMBL-EBI (MANE) transcripts retrieved from NCBI Entrez. VarSim provides programmatic functions for HGVS parsing, syntactic and semantic validation, normalization, sequence extraction, backtranslation, coordinate mapping, protein consequence prediction, genome-assembly liftover, and conversion between HGVS, VCF, and SPDI representations. We benchmarked the toolkit using 1458 HGVS descriptions across five MANE transcripts, comprising 500 coding single-nucleotide variants, 250 frameshift insertions/deletions, and 708 intronic splice-site substitutions. All 1458 descriptions passed VarSim syntactic validation, and all 750 coding descriptions passed semantic validation against the corresponding reference sequences. VariantValidator accepted all 1458 descriptions, whereas the Mutalyzer normalization endpoint processed the 750 coding descriptions. VarSim normalization agreed with Mutalyzer for all 750 coding variants and with VariantValidator for 749 of 750 variants. Protein consequence predictions agreed with VariantValidator for all 500 coding single-nucleotide variants. Format conversion between HGVS, VCF, and SPDI was exact for the tested variants, whereas transcript-to-genome projection showed substantial discrepancies relative to VariantValidator and therefore remains a limitation of the current implementation. VarSim provides a complementary, programmatic framework for reproducible HGVS processing and variant representation interoperability.

Indexed as

Computational BiologyGenetic VariationGenome, HumanGenomicsSoftwareDatabases, GeneticHumansPolymorphism, Single NucleotideReproducibility of ResultsbioinformaticsHGVS nomenclatureMANEvariant normalizationvariant validation

Identifiers

PMID42859656
PMCPMC13653078

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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.