CITE-seq data from human postnatal thymocytes (Yayon, Kedlian & Boehme et al. Nature 2024)

This shiny app allows the visualisation of 143-plex CITE-seq data of human postnatal thymocytes obtained from five donors.

This data is part of the Human Thymus Spatial Atlas by Yayon, Kedlian & Boehme et al. published in Nature in 2024, doi:10.1038/s41586-024-07944-6
Please refer to the manuscript for details on experimental procedures, antibody information, and data processing.
The raw and processed data as well as a Seurat object containing annotations and relevant meta data can be downloaded from GEO under accession GSE271304.
CITE-seq data was generated, processed and prepared for visualisation by the Taghon lab (Ghent University, Belgium).

For questions and remarks, please reach out on the Taghonlab website

Visualise cell meta data and gene / surface marker expression side-by-side on the WNN-integrated UMAP.

For transcripts, append gene name with ‘-RNA’; for surface proteins, append protein name with ‘-ADT’.

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Cell information

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Cell numbers / statistics

Gene expression

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Visualise two types of cell meta data side-by-side on the WNN-integrated UMAP.



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Cell information 1

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Cell information 2

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Visualise expression of two genes / surface markers side-by-side on the WNN-integrated UMAP.

For transcripts, append gene name with ‘-RNA’; for surface proteins, append protein name with ‘-ADT’.

Dimension Reduction

Gene expression 1

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Gene expression 2

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Visualise co-expression of two genes / surface markers on the WNN-integrated UMAP.

For transcripts, append gene name with ‘-RNA’; for surface proteins, append protein name with ‘-ADT’.

Dimension Reduction

Gene Expression

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Visualise gene / surface marker expression or continuous cell information (e.g. lineage pseudotime, number of UMIs) across groups of cells (e.g. donors / cell types).

For transcripts, append gene name with ‘-RNA’; for surface proteins, append protein name with ‘-ADT’.





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Visualise the composition of the data set across two types of discrete cell information (e.g. annotation vs. cell cycle phase).





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Visualise the gene expression patterns of multiple genes or surface markers grouped by categorical cell information (e.g. annotation).

Levels represent mean pseudobulk expression for log-normalised (RNA) or denoised & back-ground scaled (ADT) data.

Note that for ADT data, outliers can distort the visualisation in this type of plot; we instead recommend using the Violin/Boxplot visualisation.






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