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TCR_Explore: A novel webtool for T cell receptor repertoire analysis
T cells expressing either alpha-beta or gamma-delta T cell receptors (TCR) are critical sentinels of the adaptive immune system, with receptor diversity being essential for protective immunity against a broad array of pathogens and agents. Programs available to profile TCR clonotypic signatures can...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9939424/ https://www.ncbi.nlm.nih.gov/pubmed/36814721 http://dx.doi.org/10.1016/j.csbj.2023.01.046 |
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author | Mullan, Kerry A. Zhang, Justin B. Jones, Claerwen M. Goh, Shawn J.R. Revote, Jerico Illing, Patricia T. Purcell, Anthony W. La Gruta, Nicole L. Li, Chen Mifsud, Nicole A. |
author_facet | Mullan, Kerry A. Zhang, Justin B. Jones, Claerwen M. Goh, Shawn J.R. Revote, Jerico Illing, Patricia T. Purcell, Anthony W. La Gruta, Nicole L. Li, Chen Mifsud, Nicole A. |
author_sort | Mullan, Kerry A. |
collection | PubMed |
description | T cells expressing either alpha-beta or gamma-delta T cell receptors (TCR) are critical sentinels of the adaptive immune system, with receptor diversity being essential for protective immunity against a broad array of pathogens and agents. Programs available to profile TCR clonotypic signatures can be limiting for users with no coding expertise. Current analytical pipelines can be inefficient due to manual processing steps, open to data entry errors and have multiple analytical tools with unique inputs that require coding expertise. Here we present a bespoke webtool designed for users irrespective of coding expertise, coined ‘TCR_Explore’, enabling analysis either derived via Sanger sequencing or next generation sequencing (NGS) platforms. Further, TCR_Explore incorporates automated quality control steps for Sanger sequencing. The creation of flexible and publication ready figures are enabled for different sequencing platforms following universal conversion to the TCR_Explore file format. TCR_Explore will enhance a user’s capacity to undertake in-depth TCR repertoire analysis of both new and pre-existing datasets for identification of T cell clonotypes associated with health and disease. The web application is located at https://tcr-explore.erc.monash.edu for users to interactively explore TCR repertoire datasets. |
format | Online Article Text |
id | pubmed-9939424 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-99394242023-02-21 TCR_Explore: A novel webtool for T cell receptor repertoire analysis Mullan, Kerry A. Zhang, Justin B. Jones, Claerwen M. Goh, Shawn J.R. Revote, Jerico Illing, Patricia T. Purcell, Anthony W. La Gruta, Nicole L. Li, Chen Mifsud, Nicole A. Comput Struct Biotechnol J Software/Web server Article T cells expressing either alpha-beta or gamma-delta T cell receptors (TCR) are critical sentinels of the adaptive immune system, with receptor diversity being essential for protective immunity against a broad array of pathogens and agents. Programs available to profile TCR clonotypic signatures can be limiting for users with no coding expertise. Current analytical pipelines can be inefficient due to manual processing steps, open to data entry errors and have multiple analytical tools with unique inputs that require coding expertise. Here we present a bespoke webtool designed for users irrespective of coding expertise, coined ‘TCR_Explore’, enabling analysis either derived via Sanger sequencing or next generation sequencing (NGS) platforms. Further, TCR_Explore incorporates automated quality control steps for Sanger sequencing. The creation of flexible and publication ready figures are enabled for different sequencing platforms following universal conversion to the TCR_Explore file format. TCR_Explore will enhance a user’s capacity to undertake in-depth TCR repertoire analysis of both new and pre-existing datasets for identification of T cell clonotypes associated with health and disease. The web application is located at https://tcr-explore.erc.monash.edu for users to interactively explore TCR repertoire datasets. Research Network of Computational and Structural Biotechnology 2023-02-03 /pmc/articles/PMC9939424/ /pubmed/36814721 http://dx.doi.org/10.1016/j.csbj.2023.01.046 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Software/Web server Article Mullan, Kerry A. Zhang, Justin B. Jones, Claerwen M. Goh, Shawn J.R. Revote, Jerico Illing, Patricia T. Purcell, Anthony W. La Gruta, Nicole L. Li, Chen Mifsud, Nicole A. TCR_Explore: A novel webtool for T cell receptor repertoire analysis |
title | TCR_Explore: A novel webtool for T cell receptor repertoire analysis |
title_full | TCR_Explore: A novel webtool for T cell receptor repertoire analysis |
title_fullStr | TCR_Explore: A novel webtool for T cell receptor repertoire analysis |
title_full_unstemmed | TCR_Explore: A novel webtool for T cell receptor repertoire analysis |
title_short | TCR_Explore: A novel webtool for T cell receptor repertoire analysis |
title_sort | tcr_explore: a novel webtool for t cell receptor repertoire analysis |
topic | Software/Web server Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9939424/ https://www.ncbi.nlm.nih.gov/pubmed/36814721 http://dx.doi.org/10.1016/j.csbj.2023.01.046 |
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