CAVES: A Novel Tool for Comparative Analysis of Variant Epitope Sequences
In silico methods for immune epitope prediction have become essential for vaccine and therapeutic design, but manual intra-species comparison of putative epitopes remains challenging and subject to human error. Created initially for analyzing SARS-CoV-2 variants of concern, comparative analysis of v...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Viruses |
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| Online Access: | https://www.mdpi.com/1999-4915/14/6/1152 |
| _version_ | 1797481457581555712 |
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| author | Katherine Li Connor Lowey Paul Sandstrom Hezhao Ji |
| author_facet | Katherine Li Connor Lowey Paul Sandstrom Hezhao Ji |
| author_sort | Katherine Li |
| collection | DOAJ |
| description | In silico methods for immune epitope prediction have become essential for vaccine and therapeutic design, but manual intra-species comparison of putative epitopes remains challenging and subject to human error. Created initially for analyzing SARS-CoV-2 variants of concern, comparative analysis of variant epitope sequences (CAVES) is a novel tool designed to carry out rapid comparative analyses of epitopes amongst closely related pathogens, substantially reducing the required time and user workload. CAVES applies a two-level analysis approach. The Level-one (L1) analysis compares two epitope prediction files, and the Level-two (L2) analysis incorporates search results from the IEDB database of experimentally confirmed epitopes. Both L1 and L2 analyses sort epitopes into categories of exact matches, partial matches, or novel epitopes based on the degree to which they match with peptides from the compared file. Furthermore, CAVES uses positional sequence data to improve its accuracy and speed, taking only a fraction of the time required by manual analyses and minimizing human error. CAVES is widely applicable for evolutionary analyses and antigenic comparisons of any closely related pathogen species. CAVES is open-source software that runs through a graphical user interface on Windows operating systems, making it widely accessible regardless of coding expertise. The CAVES source code and test dataset presented here are publicly available on the CAVES GitHub page. |
| first_indexed | 2024-03-09T22:14:53Z |
| format | Article |
| id | doaj.art-028732ebc7c746bab5797d6dc080b062 |
| institution | Directory Open Access Journal |
| issn | 1999-4915 |
| language | English |
| last_indexed | 2024-03-09T22:14:53Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Viruses |
| spelling | doaj.art-028732ebc7c746bab5797d6dc080b0622023-11-23T19:24:28ZengMDPI AGViruses1999-49152022-05-01146115210.3390/v14061152CAVES: A Novel Tool for Comparative Analysis of Variant Epitope SequencesKatherine Li0Connor Lowey1Paul Sandstrom2Hezhao Ji3National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, MB R3E 3L5, CanadaIndependent Researcher, 208 Park West Drive, Winnipeg, MB R3Y 0T4, CanadaNational Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, MB R3E 3L5, CanadaNational Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, MB R3E 3L5, CanadaIn silico methods for immune epitope prediction have become essential for vaccine and therapeutic design, but manual intra-species comparison of putative epitopes remains challenging and subject to human error. Created initially for analyzing SARS-CoV-2 variants of concern, comparative analysis of variant epitope sequences (CAVES) is a novel tool designed to carry out rapid comparative analyses of epitopes amongst closely related pathogens, substantially reducing the required time and user workload. CAVES applies a two-level analysis approach. The Level-one (L1) analysis compares two epitope prediction files, and the Level-two (L2) analysis incorporates search results from the IEDB database of experimentally confirmed epitopes. Both L1 and L2 analyses sort epitopes into categories of exact matches, partial matches, or novel epitopes based on the degree to which they match with peptides from the compared file. Furthermore, CAVES uses positional sequence data to improve its accuracy and speed, taking only a fraction of the time required by manual analyses and minimizing human error. CAVES is widely applicable for evolutionary analyses and antigenic comparisons of any closely related pathogen species. CAVES is open-source software that runs through a graphical user interface on Windows operating systems, making it widely accessible regardless of coding expertise. The CAVES source code and test dataset presented here are publicly available on the CAVES GitHub page.https://www.mdpi.com/1999-4915/14/6/1152comparative genomicsantigenic variationevolutionbioinformaticscomputational biologysequence analysis |
| spellingShingle | Katherine Li Connor Lowey Paul Sandstrom Hezhao Ji CAVES: A Novel Tool for Comparative Analysis of Variant Epitope Sequences Viruses comparative genomics antigenic variation evolution bioinformatics computational biology sequence analysis |
| title | CAVES: A Novel Tool for Comparative Analysis of Variant Epitope Sequences |
| title_full | CAVES: A Novel Tool for Comparative Analysis of Variant Epitope Sequences |
| title_fullStr | CAVES: A Novel Tool for Comparative Analysis of Variant Epitope Sequences |
| title_full_unstemmed | CAVES: A Novel Tool for Comparative Analysis of Variant Epitope Sequences |
| title_short | CAVES: A Novel Tool for Comparative Analysis of Variant Epitope Sequences |
| title_sort | caves a novel tool for comparative analysis of variant epitope sequences |
| topic | comparative genomics antigenic variation evolution bioinformatics computational biology sequence analysis |
| url | https://www.mdpi.com/1999-4915/14/6/1152 |
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