TRIP - T cell receptor/immunoglobulin profiler
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SOFTWARE
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TRIP - T cell receptor/immunoglobulin profiler Maria Th. Kotouza1 , Katerina Gemenetzi2 , Chrysi Galigalidou2 , Elisavet Vlachonikola2 , Nikolaos Pechlivanis2 , Andreas Agathangelidis2 , Raphael Sandaltzopoulos3 , Pericles A. Mitkas1 , Kostas Stamatopoulos2 , Anastasia Chatzidimitriou2 , and Fotis E. Psomopoulos2,4* , on behalf of the Hellenic Precision Medicine Network in Oncology *Correspondence: [email protected] 2 Institute of Applied Biosciences, Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece 4 Dept of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden Full list of author information is available at the end of the article
Abstract 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_-_Tcell_Receptor_Immunoglobulin_Profiler. Keywords: Antigen receptor, Software pipeline, R shiny
© 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(
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