ArticleBMC medical genomics2020
Exploring and analysing single cell multi-omics data with VDJView.
Article in BMC medical genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 21 citations in OpenAlex.
- Current landscape of single-cell genomics in meningioma.Neuro-oncology advances · 2026Review
- Maternal Helminth Infection Causes Dysfunctional B Cell Development in Male Offspring.Journal of immunology (Baltimore, Md. : 1950) · 2024Article
- Tutorial: implementing and visualizing machine learning (ML) clinical prediction models into web-accessible calculators using Shiny R.Annals of translational medicine · 2022Article
- Machine Learning Approaches to TCR Repertoire Analysis.Frontiers in immunology · 2022Review
- Single-Cell Analysis and Tracking of Antigen-Specific T Cells: Integrating Paired Chain AIRR-Seq and Transcriptome Sequencing: A Method by the AIRR Community.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Gene biomarker prediction in glioma by integrating scRNA-seq data and gene regulatory network.BMC medical genomics · 2021Article
- Single cell RNA sequencing for breast cancer: present and future.Cell death discovery · 2021Review
- A Detailed Catalogue of Multi-Omics Methodologies for Identification of Putative Biomarkers and Causal Molecular Networks in Translational Cancer Research.International journal of molecular sciences · 2021Review
- Article
- Computational strategies for single-cell multi-omics integration.Computational and structural biotechnology journal · 2021Review
- High Throughput Multi-Omics Approaches for Clinical Trial Evaluation and Drug Discovery.Frontiers in immunology · 2021Review
- Role of Bioinformatics in Identifying Novel Biomarkers for Immune Cell Exhaustion and Tumor Microenvironment.Technology in cancer research & treatmentReview
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSingle cell RNA sequencing provides unprecedented opportunity to simultaneously explore the transcriptomic and immune receptor diversity of T and B cells. However, there are limited tools available that simultaneously analyse large multi-omics datasets integrated with metadata such as patient and clinical information.
resultsWe developed VDJView, which permits the simultaneous or independent analysis and visualisation of gene expression, immune receptors, and clinical metadata of both T and B cells. This tool is implemented as an easy-to-use R shiny web-application, which integrates numerous gene expression and TCR analysis tools, and accepts data from plate-based sorted or high-throughput single cell platforms. We utilised VDJView to analyse several 10X scRNA-seq datasets, including a recent dataset of 150,000 CD8
conclusionsVDJView enables researchers without profound bioinformatics skills to analyse immune scRNA-seq data, integrating and visualising this with clonality and metadata profiles, thus accelerating the process of hypothesis testing, data interpretation and discovery of cellular heterogeneity. VDJView is freely available at https://bitbucket.org/kirbyvisp/vdjview.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.