VisTCR: An Interactive Software for T Cell Repertoire Sequencing Data Analysis

Ni, Qingshan; Zhang, Jianyang; Zheng, Zihan; Chen, Gang; Christian, Laura S.; Grönholm, Juha; Yu, Hongliang; Zhou, Daxue; Zhuang, Yuan; Li, Qi-Jing; Wan, Ying

doi:10.3389/fgene.2020.00771

Cited by 8 publications

(9 citation statements)

References 26 publications

(31 reference statements)

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“…We recognized that there are other tools available for TCR-Seq analysis, however, these tools may not share the same purposes as pyTCR. For example, both VisTCR ( 13 ) and Vidjil ( 14 ) are web-based tools for TCR-Seq analysis that uses fastq files as input files. While pyTCR utilizes the tsv or csv files generated by pre-processing tools such as MiXCR to conduct post-analysis.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

pyTCR: A comprehensive and scalable solution for TCR-Seq data analysis to facilitate reproducibility and rigor of immunogenomics research

Peng

Moore²,

Vahed³

et al. 2022

Front. Immunol.

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T cell receptor (TCR) studies have grown substantially with the advancement in the sequencing techniques of T cell receptor repertoire sequencing (TCR-Seq). The analysis of the TCR-Seq data requires computational skills to run the computational analysis of TCR repertoire tools. However biomedical researchers with limited computational backgrounds face numerous obstacles to properly and efficiently utilizing bioinformatics tools for analyzing TCR-Seq data. Here we report pyTCR, a computational notebook-based solution for comprehensive and scalable TCR-Seq data analysis. Computational notebooks, which combine code, calculations, and visualization, are able to provide users with a high level of flexibility and transparency for the analysis. Additionally, computational notebooks are demonstrated to be user-friendly and suitable for researchers with limited computational skills. Our tool has a rich set of functionalities including various TCR metrics, statistical analysis, and customizable visualizations. The application of pyTCR on large and diverse TCR-Seq datasets will enable the effective analysis of large-scale TCR-Seq data with flexibility, and eventually facilitate new discoveries.

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Section: Discussionmentioning

confidence: 99%

“…Existing bioinformatics tools for TCR repertoire post-analysis are available as R packages such as VDJTools ( 11 ), Immunarch ( 12 ), and HTML programs such as VisTCR ( 13 ) and Vidjil ( 14 ). These tools enable biomedical researchers to analyze TCR-Seq data, however, multiple barriers and limitations exist.…”

Section: Introductionmentioning

confidence: 99%

pyTCR: A comprehensive and scalable solution for TCR-Seq data analysis to facilitate reproducibility and rigor of immunogenomics research

Peng

Moore²,

Vahed³

et al. 2022

Front. Immunol.

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“…While bespoke computational approaches are used by some, various immune repertoire analysis platforms are available. For example, VDJtools [55] or VisTCR [56] can be used to understand the immune repertoire by calculation and visualisation of summary statistics, pertaining to some of the parameters described in Table 2. A similar platform, ARResT [57], combines IMGT/HighV-QUEST with the analysis and visualisation of the resulting immune repertoire data.…”

Section: Analysis Of "Bulk" Tcr Repertoire Sequencingmentioning

confidence: 99%

Utility of Bulk T-Cell Receptor Repertoire Sequencing Analysis in Understanding Immune Responses to COVID-19

et al. 2022

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Measuring immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 19 (COVID-19), can rely on antibodies, reactive T cells and other factors, with T-cell-mediated responses appearing to have greater sensitivity and longevity. Because each T cell carries an essentially unique nucleic acid sequence for its T-cell receptor (TCR), we can interrogate sequence data derived from DNA or RNA to assess aspects of the immune response. This review deals with the utility of bulk, rather than single-cell, sequencing of TCR repertoires, considering the importance of study design, in terms of cohort selection, laboratory methods and analysis. The advances in understanding SARS-CoV-2 immunity that have resulted from bulk TCR repertoire sequencing are also be discussed. The complexity of sequencing data obtained by bulk repertoire sequencing makes analysis challenging, but simple descriptive analyses, clonal analysis, searches for specific sequences associated with immune responses to SARS-CoV-2, motif-based analyses, and machine learning approaches have all been applied. TCR repertoire sequencing has demonstrated early expansion followed by contraction of SARS-CoV-2-specific clonotypes, during active infection. Maintenance of TCR repertoire diversity, including the maintenance of diversity of anti-SARS-CoV-2 response, predicts a favourable outcome. TCR repertoire narrowing in severe COVID-19 is most likely a consequence of COVID-19-associated lymphopenia. It has been possible to follow clonotypic sequences longitudinally, which has been particularly valuable for clonotypes known to be associated with SARS-CoV-2 peptide/MHC tetramer binding or with SARS-CoV-2 peptide-induced cytokine responses. Closely related clonotypes to these previously identified sequences have been shown to respond with similar kinetics during infection. A possible superantigen-like effect of the SARS-CoV-2 spike protein has been identified, by means of observing V-segment skewing in patients with severe COVID-19, together with structural modelling. Such a superantigen-like activity, which is apparently absent from other coronaviruses, may be the basis of multisystem inflammatory syndrome and cytokine storms in COVID-19. Bulk TCR repertoire sequencing has proven to be a useful and cost-effective approach to understanding interactions between SARS-CoV-2 and the human host, with the potential to inform the design of therapeutics and vaccines, as well as to provide invaluable pathogenetic and epidemiological insights.

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“…Other studies using scRNA-seq have also focused on depicting differentiation single-cell states, pro and antitumor function of immune cell and their distributions in cancer (50). Furthermore, the ability to define the TCR sequence at a singlecell level enabled to analyze the association between therapeutic response and activation states of specific T cell clusters (51,52). Then, the development of single-cell transcriptomic technology enables to analyze the heterogeneity of immune subsets within the TME and emerges as powerful tools to screen immunerelated signatures and identify potential biomarker which may as prognostic factors or therapeutic targets (53)(54)(55).…”

Section: Applications Of Scrna-seq: Deciphering Functional Diversity mentioning

confidence: 99%

Lymphoma Heterogeneity Unraveled by Single-Cell Transcriptomics

et al. 2021

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High-definition transcriptomic studies through single-cell RNA sequencing (scRNA-Seq) have revealed the heterogeneity and functionality of the various microenvironments across numerous solid tumors. Those pioneer studies have highlighted different cellular signatures correlated with clinical response to immune checkpoint inhibitors. scRNA-Seq offers also a unique opportunity to unravel the intimate heterogeneity of the ecosystems across different lymphoma entities. In this review, we will first cover the basics and future developments of the technology, and we will discuss its input in the field of translational lymphoma research, from determination of cell-of-origin and functional diversity, to monitoring of anti-cancer targeted drugs response and toxicities, and how new improvements in both data collection and interpretation will further foster precision medicine in the upcoming years.

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VisTCR: An Interactive Software for T Cell Repertoire Sequencing Data Analysis

Cited by 8 publications

References 26 publications

pyTCR: A comprehensive and scalable solution for TCR-Seq data analysis to facilitate reproducibility and rigor of immunogenomics research

pyTCR: A comprehensive and scalable solution for TCR-Seq data analysis to facilitate reproducibility and rigor of immunogenomics research

Utility of Bulk T-Cell Receptor Repertoire Sequencing Analysis in Understanding Immune Responses to COVID-19

Lymphoma Heterogeneity Unraveled by Single-Cell Transcriptomics

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