scOrange Workflows

Data Visualization with t-SNE

Loads the data from scOrange’s single-cell datasets server and feed it into a spreadsheet viewer and t-SNE visualization. To see the raw data, double click on the Data Table widget. Or double click on the t-SNE widget for the display of cell landscape.

Multi-Sample Loader

Load Data widget reads the data from tab or comma delimited text files or annotated 10x Genomics data files. Drag-and-drop to create a list of files to load. Use cell or gene sampling, if required. The loader creates a single data set and marks the cells according to the data source.

Tags: Data

Marker Genes and Subpopulations

This workflow uses Score Cell and Marker Genes widget to score the cells according to the expression of selected markers. Scored cells can be passed to, say, t-SNE visualization, where any change of a selection of marker genes will automatically trigger the update in t-SNE to identify an associated subpopulation of cells.

Clustering and t-SNE

Load the data, cluster, and explore the clustering structure in the t-SNE embedding. Select a subset of cells in the embedding to examine their type in the Box Plot.