IMSEQ—a fast and error aware approach to immunogenetic sequence analysis

Kuchenbecker, Léon; Nienen, Mikalai; Hecht, Jochen; Neumann, Avidan U.; Babel, Nina; Reinert, Knut; Robinson, Peter N.

doi:10.1093/bioinformatics/btv309

Cited by 92 publications

(80 citation statements)

References 21 publications

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“…The clonotype calls are generated using the IMSEQ software (11). The main tasks of IMSEQ are to align the reads to model V-region and J-region sequences, extract the CDR3 region sequence, and cluster together highly similar CDR3 sequences that likely came from the same input sample clones.…”

Section: Methodsmentioning

confidence: 99%

“…We are using both the “quality-score clustering” and the “simple edit-distance clustering” with edit distance < = 2 (the IMSEQ default). The main idea here is that reads that contain highly similar CDR3 sequences are putatively from the same clone in the sample, so they are grouped together to generate one CDR3 call, as described previously (11). …”

Section: Methodsmentioning

confidence: 99%

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TCR Analyses of Two Vast and Shared Melanoma Antigen-Specific T Cell Repertoires: Common and Specific Features

Simon

Cruard

et al. 2018

Front. Immunol.

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Among Immunotherapeutic approaches for cancer treatment, the adoptive transfer of antigen specific T cells is still a relevant approach, that could have higher efficacy when further combined with immune check-point blockade. A high number of adoptive transfer trials have been performed in metastatic melanoma, due to its high immunogenic potential, either with polyclonal TIL or antigen-specific polyclonal populations. In this setting, the extensive characterization of T cell functions and receptor diversity of infused polyclonal T cells is required, notably for monitoring purposes. We developed a clinical grade procedure for the selection and amplification of polyclonal CD8 T cells, specific for two shared and widely expressed melanoma antigens: Melan-A and MELOE-1. This procedure is currently used in a clinical trial for HLA-A2 metastatic melanoma patients. In this study, we characterized the T-cell diversity (T-cell repertoire) of such T cell populations using a new RNAseq strategy. We first assessed the added-value of TCR receptor sequencing, in terms of sensitivity and specificity, by direct comparison with cytometry analysis of the T cell populations labeled with anti-Vß-specific antibodies. Results from these analyzes also confirmed specific features already reported for Melan-A and MELOE-1 specific T cell repertoires in terms of V-alpha recurrence usage, on a very high number of T cell clonotypes. Furthermore, these analyses also revealed undescribed features, such as the recurrence of a specific motif in the CDR3α region for MELOE-1 specific T cell repertoire. Finally, the analysis of a large number of T cell clonotypes originating from various patients revealed the existence of public CDR3α and ß clonotypes for Melan-A and MELOE-1 specific T cells. In conclusion, this method of high throughput TCR sequencing is a reliable and powerful approach to deeply characterize polyclonal T cell repertoires, and to reveal specific features of a given TCR repertoire, that would be useful for immune follow-up of cancer patients treated by immunotherapeutic approaches.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

TCR Analyses of Two Vast and Shared Melanoma Antigen-Specific T Cell Repertoires: Common and Specific Features

Simon

Cruard

et al. 2018

Front. Immunol.

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“…Recently, new software able to deal with up to millions of sequences have appeared: [5], IgBlast [6], Decombinator [7], miTCR [8], TCRKlass [9], MiXCR [10], IMSEQ [11]. At the heart of these programs is optimized comparison of the reads against germline databases to detect and quantify clonotypes , whose definitions are supposed to overlap as much as possible the definition of biological clones.…”

Section: Introductionmentioning

confidence: 99%

Vidjil: A Web Platform for Analysis of High-Throughput Repertoire Sequencing

et al. 2016

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BackgroundThe B and T lymphocytes are white blood cells playing a key role in the adaptive immunity. A part of their DNA, called the V(D)J recombinations, is specific to each lymphocyte, and enables recognition of specific antigenes. Today, with new sequencing techniques, one can get billions of DNA sequences from these regions. With dedicated Repertoire Sequencing (RepSeq) methods, it is now possible to picture population of lymphocytes, and to monitor more accurately the immune response as well as pathologies such as leukemia.Methods and ResultsVidjil is an open-source platform for the interactive analysis of high-throughput sequencing data from lymphocyte recombinations. It contains an algorithm gathering reads into clonotypes according to their V(D)J junctions, a web application made of a sample, experiment and patient database and a visualization for the analysis of clonotypes along the time. Vidjil is implemented in C++, Python and Javascript and licensed under the GPLv3 open-source license. Source code, binaries and a public web server are available at http://www.vidjil.org and at http://bioinfo.lille.inria.fr/vidjil. Using the Vidjil web application consists of four steps: 1. uploading a raw sequence file (typically a FASTQ); 2. running RepSeq analysis software; 3. visualizing the results; 4. annotating the results and saving them for future use. For the end-user, the Vidjil web application needs no specific installation and just requires a connection and a modern web browser. Vidjil is used by labs in hematology or immunology for research and clinical applications.

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“…In particular, PCR artefacts and sequencing errors can hamper the quantification of junctional diversity. Therefore, recent tools for TCR profiling 81 implement strategies for error correction in their analytical procedures [96][97][98][99][100][101] . Alongside 107 , which contribute to the TCR specificity.…”

Section: Tcr Profilingmentioning

confidence: 99%

Computational genomics tools for dissecting tumour–immune cell interactions

et al. 2016

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Recent breakthroughs in cancer immunotherapy and decreasing costs of high-throughput technologies have sparked intensive research into tumour-immune cell interactions using genomic tools. The wealth of the generated data and the added complexity pose considerable challenges and require computational tools to process, to analyse and to visualize the data. Recently, various tools have been developed and used to mine tumour immunologic and genomic data effectively and to provide novel mechanistic insights. Here, we review computational genomics tools for cancer immunology and provide information on the requirements and functionality in order to assist in the selection of tools and assembly of analytical pipelines.

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IMSEQ—a fast and error aware approach to immunogenetic sequence analysis

Abstract: lkuchenb@inf.fu-berlin.de or peter.robinson@charite.de.

Cited by 92 publications

References 21 publications

TCR Analyses of Two Vast and Shared Melanoma Antigen-Specific T Cell Repertoires: Common and Specific Features

TCR Analyses of Two Vast and Shared Melanoma Antigen-Specific T Cell Repertoires: Common and Specific Features

Vidjil: A Web Platform for Analysis of High-Throughput Repertoire Sequencing

Computational genomics tools for dissecting tumour–immune cell interactions

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