paraCell: a novel software tool for the interactive analysis and visualization of standard and dual host–parasite single-cell RNA-seq data
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Abstract
Advances in sequencing technology have led to a dramatic increase in the number of single-cell transcriptomic datasets. In the field of parasitology, these datasets typically describe the gene expression patterns of a given parasite species at the single-cell level under experimental conditions, in specific hosts or tissues, or at different life cycle stages. However, while this wealth of available data represents a significant resource, analysing these datasets often requires expert computational skills, preventing a considerable proportion of the parasitology community from meaningfully integrating existing single-cell data into their work. Here, we present paraCell, a novel software tool that allows the user to visualize and analyse pre-loaded single-cell data without requiring any programming ability. The source code is free to allow remote installation. On our web server, we demonstrated how to visualize and re-analyse published Plasmodium and Trypanosoma datasets. We have also generated Toxoplasma–mouse and Theileria–cow scRNA-seq datasets to highlight the functionality of paraCell for pathogen–host interaction. The analysis of the data highlights the impact of the host interferon-γ response and gene expression profiles associated with disease susceptibility by these intracellular parasites, respectively.
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- Authors
- Agboraw, E., Haese-Hill, W., Hentzschel, F., Briggs, E., Aghabi, D., Heawood, A., Harding, C. R., Shiels, B., Crouch, K., Somma, D., & Otto, T. D.
- Affiliations
- University of Glasgow (GB)
- Heidelberg University (DE)
- University of Edinburgh (GB)
- Centre National de la Recherche Scientifique (FR)
- Corresponding author
- Otto, Thomas D
- ORCID
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2025-02-08
- Volume
- 53
- Issue
- 4
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC11840555
- OpenAlex
- W4407908220
- Cited by
- 4
- References
- 46
- Citations by year
- 2026: 3 · 2025: 1
- FWCI
- 1.20
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion, cc-by-sa)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (submittedVersion, other-oa)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Newcastle University ePrints (Newcastle Univesity) (cc-by)
- Funders
- University of Montpellier (ANR-21-EXES-0005)
- Wellcome Trust (104111/Z/14/Z&A, 218288/Z/19/Z, 213455/Z/18/Z)
- University of Glasgow
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Immunology and Microbiology › Parasitology › Toxoplasma gondii Research Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- single-cell RNA sequencing, parasitology, host-pathogen interaction, interactive data visualization, Plasmodium, trypanosomes, Toxoplasma, Theileria, interferon-gamma response, disease susceptibility, gene expression profiles, web application
- MeSH terms
- RNA-Seq, Single-Cell Gene Expression Analysis, Animals, Cattle, Host-Parasite Interactions, Plasmodium, Software, Toxoplasma, Trypanosoma, Theileria, Sequence Analysis, RNA, Gene Expression Profiling, Mice, Single-Cell Analysis, Transcriptome
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