[en] [en] MOTIVATION: Single-cell RNA sequencing (scRNAseq) has transformed our ability to explore biological systems. Nevertheless, proficient expertise is essential for handling and interpreting the data.
RESULTS: In this article, we present scX, an R package built on the Shiny framework that streamlines the analysis, exploration, and visualization of single-cell experiments. With an interactive graphic interface, implemented as a web application, scX provides easy access to key scRNAseq analyses, including marker identification, gene expression profiling, and differential gene expression analysis. Additionally, scX seamlessly integrates with commonly used single-cell Seurat and SingleCellExperiment R objects, resulting in efficient processing and visualization of varied datasets. Overall, scX serves as a valuable and user-friendly tool for effortless exploration and sharing of single-cell data, simplifying some of the complexities inherent in scRNAseq analysis.
AVAILABILITY AND IMPLEMENTATION: Source code can be downloaded from https://github.com/chernolabs/scX. A docker image is available from dockerhub as chernolabs/scx.
Disciplines :
Computer science
Author, co-author :
Waichman, Tomás V ; Integrative Systems Biology Lab, Leloir Institute, Buenos Aires, CP1405, Argentina
Vercesi, M L; Integrative Systems Biology Lab, Leloir Institute, Buenos Aires, CP1405, Argentina
Berardino, Ariel A; Integrative Systems Biology Lab, Leloir Institute, Buenos Aires, CP1405, Argentina ; Instituto de Investigaciones Bioquímicas de Buenos Aires, CONICET, Buenos Aires, CP1405, Argentina
Beckel, Maximiliano S; Integrative Systems Biology Lab, Leloir Institute, Buenos Aires, CP1405, Argentina ; Instituto de Investigaciones Bioquímicas de Buenos Aires, CONICET, Buenos Aires, CP1405, Argentina
Giacomini, Damiana; Instituto de Investigaciones Bioquímicas de Buenos Aires, CONICET, Buenos Aires, CP1405, Argentina ; Laboratory of Neuronal Plasticity, Leloir Institute, Buenos Aires, CP1405, Argentina
Rasetto, Natali Belen ; Université de Liège - ULiège > Département des sciences biomédicales et précliniques ; Instituto de Investigaciones Bioquímicas de Buenos Aires, CONICET, Buenos Aires, CP1405, Argentina ; Laboratory of Neuronal Plasticity, Leloir Institute, Buenos Aires, CP1405, Argentina
Herrero, Magalí; Instituto de Investigaciones Bioquímicas de Buenos Aires, CONICET, Buenos Aires, CP1405, Argentina ; Laboratory of Neuronal Plasticity, Leloir Institute, Buenos Aires, CP1405, Argentina
Di Bella, Daniela J; Department of Stem Cells and Regenerative Biology, Harvard University, Cambridge, MA 02138, United States ; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02138, United States
Arlotta, Paola ; Department of Stem Cells and Regenerative Biology, Harvard University, Cambridge, MA 02138, United States ; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02138, United States
Schinder, Alejandro F; Instituto de Investigaciones Bioquímicas de Buenos Aires, CONICET, Buenos Aires, CP1405, Argentina ; Laboratory of Neuronal Plasticity, Leloir Institute, Buenos Aires, CP1405, Argentina
Chernomoretz, Ariel ; Integrative Systems Biology Lab, Leloir Institute, Buenos Aires, CP1405, Argentina ; Departamento de Física, FCEN, Universidad de Buenos Aires, Buenos Aires, CP1428, Argentina ; INFINA, UBA-CONICET, Buenos Aires, CP 1428, Argentina
Language :
English
Title :
scX: a user-friendly tool for scRNAseq exploration.
NINDS - National Institute of Neurological Disorders and Stroke FIC - Fogarty International Center
Funding text :
This work was supported by grants the National Institute of Neurological Disorders and Stroke (NINDS) and Fogarty International Center (FIC) (R01NS103758) to P.A. and A.F. S., and the Argentine Agency for the Promotion of Science and Technology (PICT-2020\u20130046 and PICT-2021\u20130077) to A.F.S., (PICT 2018\u201303713) to A.C. and M.S.B. (postdoctoral fellowship) and (PICT 2017\u20130389) to D.G.D.G., A.C., and A.F.S. are investigators in the Consejo Nacional de Investigaciones Cient\u00EDficas y T\u00E9cnicas (CONICET). N.B.R., A.A.B., M.H., and M.B. were supported by CONICET fellowships.
Abdulla S, Aevermann B, Assis P et al. Cz cell×gene discover: A single-cell data platform for scalable exploration, analysis and modeling of aggregated data. bioRxiv. https://doi.org/10.1101/2023.10.30. 563174, 2023, preprint: not peer reviewed.
Aussel R, Asif M, Chenag S et al. ShIVA: a user-friendly and interactive interface giving biologists control over their single-cell RNA-seq data. Sci Rep 2023;13:14377.
David FPA, Litovchenko M, Deplancke B et al. ASAP 2020 update: an open, scalable and interactive web-based portal for (single-cell) omics analyses. Nucleic Acids Res 2020;48:W403–14. 05.
Hiroyasu S, Zeglinski MR, Zhao H et al. Granzyme b inhibition reduces disease severity in autoimmune blistering diseases. Nat Commun 2021;12:302.
Jagla B, Libri V, Chica C et al. SCHNAPPs - single cell sHiNy APPlication(s). J Immunol Methods 2021;499:113176.
Lun ATL, McCarthy DJ, Marioni JC. A step-by-step workflow for low-level analysis of single-cell RNA-seq data with bioconductor. F1000Res 2016;5:2122.
Metcalfe DD, Pawankar R, Ackerman SJ et al. Biomarkers of the involvement of mast cells, basophils and eosinophils in asthma and allergic diseases. World Allergy Organ J 2016;9:7.
Miao Z, Moreno P, Huang N et al. Putative cell type discovery from single-cell gene expression data. Nat Methods 2020;17:621–8.
Miyake K, Ito J, Nakabayashi J et al. Single cell transcriptomics clarifies the basophil differentiation trajectory and identifies pre-basophils upstream of mature basophils. Nat Commun 2023;14:2694.
Ouyang JF, Kamaraj US, Cao EY et al. ShinyCell: simple and sharable visualization of single-cell gene expression data. Bioinformatics 2021;37:3374–6.
Rue-Albrecht K, Marini F, Soneson C et al. ISEE: interactive SummarizedExperiment explorer. F1000Res 2018;7:741.
Siddhuraj P, Mori M, Bjermer L et al. Distinct tryptase and cpa3-positive basophil phenotypes in healthy individuals, asthma, and copd. Eur Respiratory J 2017;50(suppl 61):OA4848.
Silva-Gomes R, Mapelli SN, Boutet M-A et al. Differential expression and regulation of MS4A family members in myeloid cells in physiological and pathological conditions. J Leukoc Biol 2021;111:817–36.
Tusi BK, Wolock SL, Weinreb C et al. Population snapshots predict early haematopoietic and erythroid hierarchies. Nature 2018;555:54–60.
Umu SU, Rapp Vander-Elst K, Karlsen VT et al. Cellsnake: a user-friendly tool for single-cell RNA sequencing analysis. Gigascience 2023;12:giad091.
Weber C, Hirst MB, Ernest B et al. SEQUIN is an R/shiny framework for rapid and reproducible analysis of RNA-seq data. Cell Rep Methods 2023;3:100420.