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Exploring and analysing single cell multi-omics data with VDJView.

Jerome Samir1,2, Simone Rizzetto1, Money Gupta1,2

  • 1School of Medical Sciences and Kirby Institute for Infection and Immunity, UNSW Sydney, Sydney, Australia.

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|February 20, 2020
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Summary
This summary is machine-generated.

VDJView is a new R shiny web-application for analyzing single-cell RNA sequencing data, integrating gene expression, immune receptors, and clinical metadata for T and B cells. This tool accelerates discovery of cellular heterogeneity and antigen-specific gene signatures without bioinformatics expertise.

Keywords:
B cell receptorImmune cellsMulti-omicsT cell receptorscRNA-seq

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Area of Science:

  • Immunology
  • Bioinformatics
  • Computational Biology

Background:

  • Single-cell RNA sequencing (scRNA-seq) offers deep insights into transcriptomic and immune receptor diversity of T and B cells.
  • Analyzing large, integrated multi-omics datasets with clinical metadata remains a challenge due to limited available tools.

Purpose of the Study:

  • To develop VDJView, an R shiny web-application for simultaneous analysis and visualization of gene expression, immune receptors, and clinical metadata in T and B cells.
  • To provide an accessible tool for researchers to analyze complex immune scRNA-seq data without requiring extensive bioinformatics expertise.

Main Methods:

  • VDJView integrates gene expression and T-cell receptor (TCR) analysis tools, accepting data from various single-cell platforms.
  • The tool was utilized to analyze large 10X scRNA-seq datasets, including CD8+ T cells with gene expression, TCR sequences, surface protein quantification, and antigen specificities.
  • Quality control, filtering, clustering, and hypothesis testing were performed to identify antigen-specific gene signatures and clonal expansion.

Main Results:

  • VDJView successfully analyzed scRNA-seq data, revealing antigen-specific gene signatures associated with T-cell differentiation and clonal expansion.
  • Analysis of T and B cells from breast cancer patients identified distinct gene signatures correlating with molecular subtypes and revealed clonally expanded cells.
  • The tool facilitated data interpretation and hypothesis testing, enabling discovery of cellular heterogeneity.

Conclusions:

  • VDJView empowers researchers with limited bioinformatics skills to analyze and visualize immune scRNA-seq data alongside clonality and metadata.
  • The application accelerates hypothesis testing, data interpretation, and the discovery of cellular heterogeneity in immune cell populations.
  • VDJView is freely available, promoting wider accessibility for advanced immune cell data analysis.