Dataset Information

ImSpectR - R package to quantify immune repertoire diversity in spectratype and repertoire sequencing data.

ABSTRACT: Summary: An effective immune system is characterized by a diverse immune repertoire. There is a strong demand for accurate and quantitative methods to assess the diversity of the immune repertoire for various (pre-)clinical applications, including the diagnosis and prognosis of primary immune deficiencies, or to assess the response to therapy. Current strategies for immune diversity assessment generally comprise the visual inspection of the length distribution of rearranged T- and B-cell receptors. Visual inspections, however, are prone to subjective assessments and thus lead to biases. Here, we introduce ImSpectR, a unified approach to quantify immunodiversity using either spectratype, repertoire sequencing or single cell RNA sequencing data. ImSpectR scores various types of deviations from the expected length distribution and integrates these into one measure, allowing for robust quantitative comparisons of immune diversity across individuals or conditions.

Availability: R-package is available for download on GitHub at https://github.com/martijn-cordes/ImSpectR.

Supplementary information: Supplementary data are available at Bioinformatics online.

SUBMITTER: Cordes M

PROVIDER: S-EPMC7703782 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

ImSpectR - R package to quantify immune repertoire diversity in spectratype and repertoire sequencing data.

Cordes Martijn M Pike-Overzet Karin K van Eggermond Marja M Vloemans Sandra S Baert Miranda R MR Garcia-Perez Laura L Staal Frank J T FJT Reinders Marcel J T MJT van den Akker Erik E

Bioinformatics (Oxford, England) 20191030

<h4>Summary</h4>An effective immune system is characterized by a diverse immune repertoire. There is a strong demand for accurate and quantitative methods to assess the diversity of the immune repertoire for various (pre-)clinical applications, including the diagnosis and prognosis of primary immune deficiencies, or to assess the response to therapy. Current strategies for immune diversity assessment generally comprise the visual inspection of the length distribution of rearranged T- and B-cell ...[more]

PMID: 31665245

Similar Datasets

Project description:BackgroundCancer immunotherapy has demonstrated significant clinical activity in different cancers. T cells represent a crucial component of the adaptive immune system and are thought to mediate anti-tumoral immunity. Antigen-specific recognition by T cells is via the T cell receptor (TCR) which is unique for each T cell. Next generation sequencing (NGS) of the TCRs can be used as a platform to profile the T cell repertoire. Though there are a number of software tools available for processing repertoire data by mapping antigen receptor segments to sequencing reads and assembling the clonotypes, most of them are not designed to track and examine the dynamic nature of the TCR repertoire across multiple time points or between different biologic compartments (e.g., blood and tissue samples) in a clinical context.ResultsWe integrated different diversity measures to assess the T cell repertoire diversity and examined the robustness of the diversity indices. Among those tested, Clonality was identified for its robustness as a key metric for study design and the first choice to measure TCR repertoire diversity. To evaluate the dynamic nature of T cell clonotypes across time, we utilized several binary similarity measures (such as Baroni-Urbani and Buser overlap index), relative clonality and Morisita's overlap index, as well as the intraclass correlation coefficient, and performed fold change analysis, which was further extended to investigate the transition of clonotypes among different biological compartments. Furthermore, the application of differential testing enabled the detection of clonotypes which were significantly changed across time. By applying the proposed "3D" analysis pipeline to the real example of prostate cancer subjects who received sipuleucel-T, an FDA-approved immunotherapy, we were able to detect changes in TCR sequence frequency and diversity thus demonstrating that sipuleucel-T treatment affected TCR repertoire in blood and in prostate tissue. We also found that the increase in common TCR sequences between tissue and blood after sipuleucel-T treatment supported the hypothesis that treatment-induced T cell migrated into the prostate tissue. In addition, a second example of prostate cancer subjects treated with Ipilimumab and granulocyte macrophage colony stimulating factor (GM-CSF) was presented in the supplementary documents to further illustrate assessing the treatment-associated change in a clinical context by the proposed workflow.ConclusionsOur paper provides guidance to study the diversity and dynamics of NGS-based TCR repertoire profiling in a clinical context to ensure consistency and reproducibility of post-analysis. This analysis pipeline will provide an initial workflow for TCR sequencing data with serial time points and for comparing T cells in multiple compartments for a clinical study.

Dataset Information

ImSpectR - R package to quantify immune repertoire diversity in spectratype and repertoire sequencing data.

Publications

ImSpectR - R package to quantify immune repertoire diversity in spectratype and repertoire sequencing data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets