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paraCell: a novel software tool for the interactive analysis and visualization of standard and dual host-parasite single cell RNA-Seq data

Title: paraCell: a novel software tool for the interactive analysis and visualization of standard and dual host-parasite single cell RNA-Seq data
Authors: Agboraw, Edward; Haese-Hill, William; Hentzschel, Franziska; Briggs, Emma; Aghabi, Dana; Heawood, Anna; Harding, Clare R.; Shiels, Brian; Crouch, Kathryn; Somma, Dommenico; Otto, Thomas
Publisher Information: Oxford University Press
Publication Year: 2025
Collection: University of Glasgow: Enlighten - Publications
Description: 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.
Document Type: article in journal/newspaper
File Description: text
Language: English
Relation: https://eprints.gla.ac.uk/348762/1/348762.pdf; Agboraw, E. et al. (2025) paraCell: a novel software tool for the interactive analysis and visualization of standard and dual host-parasite single cell RNA-Seq data. Nucleic Acids Research , 53(4), gkaf091. (doi:10.1093/nar/gkaf091 ) (PMID:39988320)
DOI: 10.1093/nar/gkaf091
Availability: https://eprints.gla.ac.uk/348762/; https://eprints.gla.ac.uk/348762/1/348762.pdf; https://doi.org/10.1093/nar/gkaf091
Rights: cc_by_4
Accession Number: edsbas.C487B774
Database: BASE