IgMAT: immunoglobulin sequence multi-species annotation tool for any species including those with incomplete antibody annotation or unusual characteristics
Background The advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and informative regardless of study species. However, to fully map dynamic changes in polyclonal responses precise framework and complementarity determi...
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| Vydáno v: | BMC bioinformatics Ročník 24; číslo 1; s. 491 - 8 |
|---|---|
| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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London
BioMed Central
21.12.2023
BioMed Central Ltd Springer Nature B.V BMC |
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| ISSN: | 1471-2105, 1471-2105 |
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| Abstract | Background
The advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and informative regardless of study species. However, to fully map dynamic changes in polyclonal responses precise framework and complementarity determining region annotation of rearranging genes is pivotal. Most sequence annotation tools are designed primarily for use with human and mouse antibody sequences which use databases with fixed species lists, applying very specific assumptions which select against unique structural characteristics. For this reason, data agnostic tools able to learn from presented data can be very useful with new species or with novel datasets.
Results
We have developed IgMAT, which utilises a reduced amino acid alphabet, that incorporates multiple HMM alignments into a single consensus to automatically annotate immunoglobulin sequences from most organisms. Additionally, the software allows the incorporation of user defined databases to better represent the species and/or antibody class of interest. To demonstrate the accuracy and utility of IgMAT, we present analysis of sequences extracted from structural data and immunoglobulin sequence datasets from several different species.
Conclusions
IgMAT is fully open-sourced and freely available on GitHub (
https://github.com/TPI-Immunogenetics/igmat
) for download under GPLv3 license. It can be used as a CLI application or as a python module to be integrated in custom scripts. |
|---|---|
| AbstractList | The advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and informative regardless of study species. However, to fully map dynamic changes in polyclonal responses precise framework and complementarity determining region annotation of rearranging genes is pivotal. Most sequence annotation tools are designed primarily for use with human and mouse antibody sequences which use databases with fixed species lists, applying very specific assumptions which select against unique structural characteristics. For this reason, data agnostic tools able to learn from presented data can be very useful with new species or with novel datasets.BACKGROUNDThe advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and informative regardless of study species. However, to fully map dynamic changes in polyclonal responses precise framework and complementarity determining region annotation of rearranging genes is pivotal. Most sequence annotation tools are designed primarily for use with human and mouse antibody sequences which use databases with fixed species lists, applying very specific assumptions which select against unique structural characteristics. For this reason, data agnostic tools able to learn from presented data can be very useful with new species or with novel datasets.We have developed IgMAT, which utilises a reduced amino acid alphabet, that incorporates multiple HMM alignments into a single consensus to automatically annotate immunoglobulin sequences from most organisms. Additionally, the software allows the incorporation of user defined databases to better represent the species and/or antibody class of interest. To demonstrate the accuracy and utility of IgMAT, we present analysis of sequences extracted from structural data and immunoglobulin sequence datasets from several different species.RESULTSWe have developed IgMAT, which utilises a reduced amino acid alphabet, that incorporates multiple HMM alignments into a single consensus to automatically annotate immunoglobulin sequences from most organisms. Additionally, the software allows the incorporation of user defined databases to better represent the species and/or antibody class of interest. To demonstrate the accuracy and utility of IgMAT, we present analysis of sequences extracted from structural data and immunoglobulin sequence datasets from several different species.IgMAT is fully open-sourced and freely available on GitHub ( https://github.com/TPI-Immunogenetics/igmat ) for download under GPLv3 license. It can be used as a CLI application or as a python module to be integrated in custom scripts.CONCLUSIONSIgMAT is fully open-sourced and freely available on GitHub ( https://github.com/TPI-Immunogenetics/igmat ) for download under GPLv3 license. It can be used as a CLI application or as a python module to be integrated in custom scripts. Background The advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and informative regardless of study species. However, to fully map dynamic changes in polyclonal responses precise framework and complementarity determining region annotation of rearranging genes is pivotal. Most sequence annotation tools are designed primarily for use with human and mouse antibody sequences which use databases with fixed species lists, applying very specific assumptions which select against unique structural characteristics. For this reason, data agnostic tools able to learn from presented data can be very useful with new species or with novel datasets. Results We have developed IgMAT, which utilises a reduced amino acid alphabet, that incorporates multiple HMM alignments into a single consensus to automatically annotate immunoglobulin sequences from most organisms. Additionally, the software allows the incorporation of user defined databases to better represent the species and/or antibody class of interest. To demonstrate the accuracy and utility of IgMAT, we present analysis of sequences extracted from structural data and immunoglobulin sequence datasets from several different species. Conclusions IgMAT is fully open-sourced and freely available on GitHub ( https://github.com/TPI-Immunogenetics/igmat ) for download under GPLv3 license. It can be used as a CLI application or as a python module to be integrated in custom scripts. The advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and informative regardless of study species. However, to fully map dynamic changes in polyclonal responses precise framework and complementarity determining region annotation of rearranging genes is pivotal. Most sequence annotation tools are designed primarily for use with human and mouse antibody sequences which use databases with fixed species lists, applying very specific assumptions which select against unique structural characteristics. For this reason, data agnostic tools able to learn from presented data can be very useful with new species or with novel datasets. We have developed IgMAT, which utilises a reduced amino acid alphabet, that incorporates multiple HMM alignments into a single consensus to automatically annotate immunoglobulin sequences from most organisms. Additionally, the software allows the incorporation of user defined databases to better represent the species and/or antibody class of interest. To demonstrate the accuracy and utility of IgMAT, we present analysis of sequences extracted from structural data and immunoglobulin sequence datasets from several different species. IgMAT is fully open-sourced and freely available on GitHub ( https://github.com/TPI-Immunogenetics/igmat ) for download under GPLv3 license. It can be used as a CLI application or as a python module to be integrated in custom scripts. BackgroundThe advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and informative regardless of study species. However, to fully map dynamic changes in polyclonal responses precise framework and complementarity determining region annotation of rearranging genes is pivotal. Most sequence annotation tools are designed primarily for use with human and mouse antibody sequences which use databases with fixed species lists, applying very specific assumptions which select against unique structural characteristics. For this reason, data agnostic tools able to learn from presented data can be very useful with new species or with novel datasets.ResultsWe have developed IgMAT, which utilises a reduced amino acid alphabet, that incorporates multiple HMM alignments into a single consensus to automatically annotate immunoglobulin sequences from most organisms. Additionally, the software allows the incorporation of user defined databases to better represent the species and/or antibody class of interest. To demonstrate the accuracy and utility of IgMAT, we present analysis of sequences extracted from structural data and immunoglobulin sequence datasets from several different species.ConclusionsIgMAT is fully open-sourced and freely available on GitHub (https://github.com/TPI-Immunogenetics/igmat) for download under GPLv3 license. It can be used as a CLI application or as a python module to be integrated in custom scripts. The advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and informative regardless of study species. However, to fully map dynamic changes in polyclonal responses precise framework and complementarity determining region annotation of rearranging genes is pivotal. Most sequence annotation tools are designed primarily for use with human and mouse antibody sequences which use databases with fixed species lists, applying very specific assumptions which select against unique structural characteristics. For this reason, data agnostic tools able to learn from presented data can be very useful with new species or with novel datasets. We have developed IgMAT, which utilises a reduced amino acid alphabet, that incorporates multiple HMM alignments into a single consensus to automatically annotate immunoglobulin sequences from most organisms. Additionally, the software allows the incorporation of user defined databases to better represent the species and/or antibody class of interest. To demonstrate the accuracy and utility of IgMAT, we present analysis of sequences extracted from structural data and immunoglobulin sequence datasets from several different species. IgMAT is fully open-sourced and freely available on GitHub (https://github.com/TPI-Immunogenetics/igmat) for download under GPLv3 license. It can be used as a CLI application or as a python module to be integrated in custom scripts. Abstract Background The advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and informative regardless of study species. However, to fully map dynamic changes in polyclonal responses precise framework and complementarity determining region annotation of rearranging genes is pivotal. Most sequence annotation tools are designed primarily for use with human and mouse antibody sequences which use databases with fixed species lists, applying very specific assumptions which select against unique structural characteristics. For this reason, data agnostic tools able to learn from presented data can be very useful with new species or with novel datasets. Results We have developed IgMAT, which utilises a reduced amino acid alphabet, that incorporates multiple HMM alignments into a single consensus to automatically annotate immunoglobulin sequences from most organisms. Additionally, the software allows the incorporation of user defined databases to better represent the species and/or antibody class of interest. To demonstrate the accuracy and utility of IgMAT, we present analysis of sequences extracted from structural data and immunoglobulin sequence datasets from several different species. Conclusions IgMAT is fully open-sourced and freely available on GitHub ( https://github.com/TPI-Immunogenetics/igmat ) for download under GPLv3 license. It can be used as a CLI application or as a python module to be integrated in custom scripts. Background The advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and informative regardless of study species. However, to fully map dynamic changes in polyclonal responses precise framework and complementarity determining region annotation of rearranging genes is pivotal. Most sequence annotation tools are designed primarily for use with human and mouse antibody sequences which use databases with fixed species lists, applying very specific assumptions which select against unique structural characteristics. For this reason, data agnostic tools able to learn from presented data can be very useful with new species or with novel datasets. Results We have developed IgMAT, which utilises a reduced amino acid alphabet, that incorporates multiple HMM alignments into a single consensus to automatically annotate immunoglobulin sequences from most organisms. Additionally, the software allows the incorporation of user defined databases to better represent the species and/or antibody class of interest. To demonstrate the accuracy and utility of IgMAT, we present analysis of sequences extracted from structural data and immunoglobulin sequence datasets from several different species. Conclusions IgMAT is fully open-sourced and freely available on GitHub ( Keywords: Immunoglobulin, Annotation, IMGT |
| ArticleNumber | 491 |
| Audience | Academic |
| Author | Maccari, Giuseppe Dorey-Robinson, Daniel Hammond, John A. |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38129777$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1126/science.1067308 10.1371/journal.pone.0190982 10.1016/S0145-305X(02)00039-3 10.1016/j.molimm.2018.11.017 10.1093/bioinformatics/btt369 10.1093/bioinformatics/btv552 10.1371/journal.pone.0161801 10.3389/fimmu.2020.605170 10.1093/nar/gku1106 10.3389/fimmu.2019.02870 10.1093/nar/gkt1043 10.1093/nar/gki010 10.1093/protein/gzg044 10.1038/cmi.2017.117 |
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| Snippet | Background
The advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and... The advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and informative... Background The advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and... BackgroundThe advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible and... Abstract Background The advent and continual improvement of high-throughput sequencing technologies has made immunoglobulin repertoire sequencing accessible... |
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| SubjectTerms | Algorithms Amino acids Animal behavior Animals Annotation Annotations Antibodies Bioinformatics Biomedical and Life Sciences Complementarity Computational Biology/Bioinformatics Computer Appl. in Life Sciences Databases, Factual Datasets Health aspects Humans IMGT Immunoglobulin Immunoglobulins Immunoglobulins - genetics Life Sciences Mice Microarrays New species Next-generation sequencing Properties Software Viral antibodies |
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| Title | IgMAT: immunoglobulin sequence multi-species annotation tool for any species including those with incomplete antibody annotation or unusual characteristics |
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