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Lookup NU author(s): Dr Emma BriggsORCiD
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Advances in sequencing technology have led to a dramatic increase in the number of single-cell transcriptomic datasets available. In the field of parasitology, these datasets typically describe the gene expression patterns of a given parasite species under specific experimental conditions, in specific hosts or tissues, or at different life-cycle stages. However, while this wealth of available data represents a significant resource for further research, the analysis of these datasets often requires significant computational skills, preventing a considerable proportion of the parasitology community from meaningfully incorporating existing single-cell data into their work. Here, we present paraCell, a novel software tool that automates the advanced analysis of published single-cell data without requiring any programming ability. On our free web server, we demonstrated how to visualise data, re-analyse published Plasmodium and Trypanosoma datasets, and present novel Toxoplasma-mouse and Theileria-cow atlases to study the impact of IFN-γ and host genetic susceptibility.
Author(s): Agboraw E, Haese-Hill W, Hentzschel F, Briggs EB, Aghabi D, Heawood H, Harding CR, Schiels B, Crouch KR, Somma D, Otto TD
Publication type: Article
Publication status: Submitted
Journal: bioRxiv
Year: 2024
Acceptance date: 30/08/2024
Publisher: Cold Spring Harbor Laboratory
URL: https://doi.org/10.1101/2024.08.29.610375
DOI: 10.1101/2024.08.29.610375
Notes: This article is a preprint and has not been certified by peer review.
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