Artikel ; Online: Fast and accurate variant identification tool for sequencing-based studies.
2024 Band 22, Heft 1, Seite(n) 90
Abstract: Background: Accurate identification of genetic variants, such as point mutations and insertions/deletions (indels), is crucial for various genetic studies into epidemic tracking, population genetics, and disease diagnosis. Genetic studies into ... ...
| Abstract | Background: Accurate identification of genetic variants, such as point mutations and insertions/deletions (indels), is crucial for various genetic studies into epidemic tracking, population genetics, and disease diagnosis. Genetic studies into microbiomes often require processing numerous sequencing datasets, necessitating variant identifiers with high speed, accuracy, and robustness. Results: We present QuickVariants, a bioinformatics tool that effectively summarizes variant information from read alignments and identifies variants. When tested on diverse bacterial sequencing data, QuickVariants demonstrates a ninefold higher median speed than bcftools, a widely used variant identifier, with higher accuracy in identifying both point mutations and indels. This accuracy extends to variant identification in virus samples, including SARS-CoV-2, particularly with significantly fewer false negative indels than bcftools. The high accuracy of QuickVariants is further demonstrated by its detection of a greater number of Omicron-specific indels (5 versus 0) and point mutations (61 versus 48-54) than bcftools in sewage metagenomes predominated by Omicron variants. Much of the reduced accuracy of bcftools was attributable to its misinterpretation of indels, often producing false negative indels and false positive point mutations at the same locations. Conclusions: We introduce QuickVariants, a fast, accurate, and robust bioinformatics tool designed for identifying genetic variants for microbial studies. QuickVariants is available at https://github.com/caozhichongchong/QuickVariants . |
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| Mesh-Begriff(e) | SARS-CoV-2/genetics ; INDEL Mutation ; Computational Biology/methods ; Humans ; Software ; COVID-19/virology ; High-Throughput Nucleotide Sequencing/methods ; Point Mutation ; Genetic Variation ; Sequence Analysis, DNA/methods |
| Sprache | Englisch |
| Erscheinungsdatum | 2024-04-22 |
| Erscheinungsland | England |
| Dokumenttyp | Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't |
| ZDB-ID | 2133020-7 |
| ISSN | 1741-7007 ; 1741-7007 |
| ISSN (online) | 1741-7007 |
| ISSN | 1741-7007 |
| DOI | 10.1186/s12915-024-01891-4 |
| Datenquelle | MEDical Literature Analysis and Retrieval System OnLINE |
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