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TRIP - T cell receptor/immunoglobulin profiler
BACKGROUND: Antigen receptors are characterized by an extreme diversity of specificities, which poses major computational and analytical challenges, particularly in the era of high-throughput immunoprofiling by next generation sequencing (NGS). The T cell Receptor/Immunoglobulin Profiler (TRIP) tool...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7525938/ https://www.ncbi.nlm.nih.gov/pubmed/32993478 http://dx.doi.org/10.1186/s12859-020-03669-1 |
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author | Kotouza, Maria Th. Gemenetzi, Katerina Galigalidou, Chrysi Vlachonikola, Elisavet Pechlivanis, Nikolaos Agathangelidis, Andreas Sandaltzopoulos, Raphael Mitkas, Pericles A. Stamatopoulos, Kostas Chatzidimitriou, Anastasia Psomopoulos, Fotis E. |
author_facet | Kotouza, Maria Th. Gemenetzi, Katerina Galigalidou, Chrysi Vlachonikola, Elisavet Pechlivanis, Nikolaos Agathangelidis, Andreas Sandaltzopoulos, Raphael Mitkas, Pericles A. Stamatopoulos, Kostas Chatzidimitriou, Anastasia Psomopoulos, Fotis E. |
author_sort | Kotouza, Maria Th. |
collection | PubMed |
description | BACKGROUND: Antigen receptors are characterized by an extreme diversity of specificities, which poses major computational and analytical challenges, particularly in the era of high-throughput immunoprofiling by next generation sequencing (NGS). The T cell Receptor/Immunoglobulin Profiler (TRIP) tool offers the opportunity for an in-depth analysis based on the processing of the output files of the IMGT/HighV-Quest tool, a standard in NGS immunoprofiling, through a number of interoperable modules. These provide detailed information about antigen receptor gene rearrangements, including variable (V), diversity (D) and joining (J) gene usage, CDR3 amino acid and nucleotide composition and clonality of both T cell receptors (TR) and B cell receptor immunoglobulins (BcR IG), and characteristics of the somatic hypermutation within the BcR IG genes. TRIP is a web application implemented in R shiny. RESULTS: Two sets of experiments have been performed in order to evaluate the efficiency and performance of the TRIP tool. The first used a number of synthetic datasets, ranging from 250k to 1M sequences, and established the linear response time of the tool (about 6 h for 1M sequences processed through the entire BcR IG data pipeline). The reproducibility of the tool was tested comparing the results produced by the main TRIP workflow with the results from a previous pipeline used on the Galaxy platform. As expected, no significant differences were noted between the two tools; although the preselection process seems to be stricter within the TRIP pipeline, about 0.1% more rearrangements were filtered out, with no impact on the final results. CONCLUSIONS: TRIP is a software framework that provides analytical services on antigen receptor gene sequence data. It is accurate and contains functions for data wrangling, cleaning, analysis and visualization, enabling the user to build a pipeline tailored to their needs. TRIP is publicly available at https://bio.tools/TRIP_-_T-cell_Receptor_Immunoglobulin_Profiler. |
format | Online Article Text |
id | pubmed-7525938 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-75259382020-09-30 TRIP - T cell receptor/immunoglobulin profiler Kotouza, Maria Th. Gemenetzi, Katerina Galigalidou, Chrysi Vlachonikola, Elisavet Pechlivanis, Nikolaos Agathangelidis, Andreas Sandaltzopoulos, Raphael Mitkas, Pericles A. Stamatopoulos, Kostas Chatzidimitriou, Anastasia Psomopoulos, Fotis E. BMC Bioinformatics Software BACKGROUND: Antigen receptors are characterized by an extreme diversity of specificities, which poses major computational and analytical challenges, particularly in the era of high-throughput immunoprofiling by next generation sequencing (NGS). The T cell Receptor/Immunoglobulin Profiler (TRIP) tool offers the opportunity for an in-depth analysis based on the processing of the output files of the IMGT/HighV-Quest tool, a standard in NGS immunoprofiling, through a number of interoperable modules. These provide detailed information about antigen receptor gene rearrangements, including variable (V), diversity (D) and joining (J) gene usage, CDR3 amino acid and nucleotide composition and clonality of both T cell receptors (TR) and B cell receptor immunoglobulins (BcR IG), and characteristics of the somatic hypermutation within the BcR IG genes. TRIP is a web application implemented in R shiny. RESULTS: Two sets of experiments have been performed in order to evaluate the efficiency and performance of the TRIP tool. The first used a number of synthetic datasets, ranging from 250k to 1M sequences, and established the linear response time of the tool (about 6 h for 1M sequences processed through the entire BcR IG data pipeline). The reproducibility of the tool was tested comparing the results produced by the main TRIP workflow with the results from a previous pipeline used on the Galaxy platform. As expected, no significant differences were noted between the two tools; although the preselection process seems to be stricter within the TRIP pipeline, about 0.1% more rearrangements were filtered out, with no impact on the final results. CONCLUSIONS: TRIP is a software framework that provides analytical services on antigen receptor gene sequence data. It is accurate and contains functions for data wrangling, cleaning, analysis and visualization, enabling the user to build a pipeline tailored to their needs. TRIP is publicly available at https://bio.tools/TRIP_-_T-cell_Receptor_Immunoglobulin_Profiler. BioMed Central 2020-09-29 /pmc/articles/PMC7525938/ /pubmed/32993478 http://dx.doi.org/10.1186/s12859-020-03669-1 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visithttp://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Kotouza, Maria Th. Gemenetzi, Katerina Galigalidou, Chrysi Vlachonikola, Elisavet Pechlivanis, Nikolaos Agathangelidis, Andreas Sandaltzopoulos, Raphael Mitkas, Pericles A. Stamatopoulos, Kostas Chatzidimitriou, Anastasia Psomopoulos, Fotis E. TRIP - T cell receptor/immunoglobulin profiler |
title | TRIP - T cell receptor/immunoglobulin profiler |
title_full | TRIP - T cell receptor/immunoglobulin profiler |
title_fullStr | TRIP - T cell receptor/immunoglobulin profiler |
title_full_unstemmed | TRIP - T cell receptor/immunoglobulin profiler |
title_short | TRIP - T cell receptor/immunoglobulin profiler |
title_sort | trip - t cell receptor/immunoglobulin profiler |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7525938/ https://www.ncbi.nlm.nih.gov/pubmed/32993478 http://dx.doi.org/10.1186/s12859-020-03669-1 |
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