Vitessce R Shiny app demonstrating integrative and interactive visualization of single-cell data with Vitessce (Visual integration tool for exploration of spatial single cell experiments).
The Demo tab shows examples of Vitessce visualizations for sample datasets (for information on the datasets, see Datasets section below).
The Run analysis tab allows for tailored analysis of Vitessce visualizations for sample single-cell datasets and user-uploaded, single-cell datasets.
Sample datasets (Input data = "Select example dataset"): Upon choosing an sample dataset, the analysis can be tailored by filtering the dataset (using min.cells, min.features, and percent.mt) and by customizing the Vitessce visualization (selecting the analyses, summaries, descriptions, and view options to display for the dataset). If dataset filtering results in a dataset that is too large, the Shiny app will disconnect from the <shinyapps.io> server. Occasionally, when toggling between tabs, visualizations may appear distorted. This can be fixed by zooming in and then zooming out of the page.
User-uploaded datasets (Input data = "Upload dataset"): Users can also upload a single-cell dataset in the form of an .rds file containing the single-cell dataset as a SeuratObject. For examples of the file format, see "Run analysis datasets" (datasets ending in "_full.rds") under Datasets. Upon uploading the single-cell dataset, the analysis can be performed in the same way as that for sample datasets described above. To further customize single-cell data analysis and visualization, see Vitessce.
Sample datasets were obtained from the following sources:
- Peripheral blood mononuclear cells (PBMC) -- 10X Genomics https://support.10xgenomics.com/single-cell-gene-expression/datasets/1.1.0/pbmc3k
- CD4 T cells -- Zheng, G., Terry, J., Belgrader, P. et al. Massively parallel digital transcriptional profiling of single cells. Nat Commun 8, 14049 (2017).
- CD8 T cells -- Zheng, G., Terry, J., Belgrader, P. et al. Massively parallel digital transcriptional profiling of single cells. Nat Commun 8, 14049 (2017).
- Non-small cell lung cancer cells -- 10X Genomics https://support.10xgenomics.com/single-cell-vdj/datasets/2.2.0/vdj_v1_hs_nsclc_5gex
data-processing.R contains code used to process the raw data. The processed datasets can be found at the following links:
Demo datasets
- https://vitessce-export-examples.s3.amazonaws.com/shiny-app/data_pbmc_results.rds
- https://vitessce-export-examples.s3.amazonaws.com/shiny-app/data_tcellcd4_results.rds
- https://vitessce-export-examples.s3.amazonaws.com/shiny-app/data_tcellcd8_results.rds
- https://vitessce-export-examples.s3.amazonaws.com/shiny-app/data_nsclc_results.rds
Run analysis datasets
- https://vitessce-export-examples.s3.amazonaws.com/shiny-app/data_pbmc_full.rds
- https://vitessce-export-examples.s3.amazonaws.com/shiny-app/data_tcellcd4_full.rds
- https://vitessce-export-examples.s3.amazonaws.com/shiny-app/data_tcellcd8_full.rds
- https://vitessce-export-examples.s3.amazonaws.com/shiny-app/data_nsclc_full.rds
The Vitessce R Shiny app embeds Vitessce in an R Shiny app (code in app.R). For a simpler example of using Vitessce in an R Shiny app, see here.
The Vitessce R Shiny app is hosted by the shinyapp.io server at https://gehlenborglab.shinyapps.io/vitessce-shiny/.