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Correction: CITEViz: interactively classify cell populations in CITE-Seq via a flow cytometry-like gating workflow using R-Shiny
- Garth L. Kong 1 na1 ,
- Thai T. Nguyen 1 na1 ,
- Wesley K. Rosales 2 na1 ,
- Anjali D. Panikar 3 na1 ,
- John H. W. Cheney 3 na1 ,
- Theresa A. Lusardi 4 ,
- William M. Yashar 1,5 ,
- Brittany M. Curtiss 1 ,
- Sarah A. Carratt 1 ,
- Theodore P. Braun 1,6 &
- ...
- Julia E. Maxson 1
BMC Bioinformatics volume 26, Article number: 244 (2025) Cite this article
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The Original Article was published on 02 April 2024
Correction to: BMC Bioinformatics (2024) 25:142 https://doi.org/10.1186/s12859-024-05762-1
Following the publication of the original article [1], the authors would like to correct Table 1 and the sentence under the sub-heading CITEViz compared to other programs.
The correct Table 1 is given below:
Discussions
CITEViz compared to other programs
The sentence currently reads: Another similar tool is the Interactive SummarizedExperiment Explorer (iSEE). iSEE is an R-Shiny package from BioConductor that provides a visual interface to explore single-cell datasets, but it lacks an iterative filtration feature that is essential to recreate the flow cytometry gating workflow [13].
The sentence should read: Another similar tool is the Interactive SummarizedExperiment Explorer (iSEE). iSEE is an R-Shiny package from BioConductor that provides a visual interface to explore single-cell dataset and apply the flow cytometry workflow with minor adjustment of the layout [14]. iSEE was originally optimized for CyTOF and scRNA-Seq data in SingleCellExperiment format but is incompatible with the multi-assay structure of CITE-Seq datasets. To aid users in choosing a particular tool, the main advantage of CITEViz is to implement the gating workflow in CITE-Seq data in native Seurat format via a simplified layout. Users who are looking for a multi-dimensional, tailored exploration of their data with a customizable layout should consider iSEE.
The original article [1] has been corrected.
Reference
Kong et al. CITEViz: interactively classify cell populations in CITE-Seq via a flow cytometry-like gating workflow using R-Shiny. BMC Bioinformatics. 2024;25:142. https://doi.org/10.1186/s12859-024-05762-1
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Kong, G.L., Nguyen, T.T., Rosales, W.K. et al. Correction: CITEViz: interactively classify cell populations in CITE-Seq via a flow cytometry-like gating workflow using R-Shiny. BMC Bioinformatics 26, 244 (2025). https://doi.org/10.1186/s12859-025-06274-2
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DOI: https://doi.org/10.1186/s12859-025-06274-2
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