This app is designed to aid in the analysis of single-cell RNA-seq data collected from the following studies:
Yan et al., Blakeley et al., Petropoulos et al. and Messmer et al.
For a detailed list of the samples that we used
Select which datasets you would like to inspect and click 'Load Data' to begin. When more than one set is selected they will be integrated together.
Genes on KEGG pathway diagrams are coloured according to their expression in the different cell types. As a result, rectangles on the KEGG diagram are coloured with the median expression of the gene across single cells of the same type. When rectangles represent more than one gene, the maximum median is represented. Clicking on a rectangle generates boxplots with the expression distribution of the gene or genes in the cell types present in the loaded data. The box plot representing the gene being used to colour the group is highlighted with a red border.
This page allows you to plot the single-cell data using either PCA or UMAP. Each point on the plot represents a cell in the data. Choose to colour by gene expression and select a gene to colour each cell by how much it expressed that particular gene. You can select genes by clicking them in the dropdown or by typing in the gene name and selecting it.
Select up to 8 genes to view their expression distribution in the cell types present in the loaded data. You can select genes by clicking them in the dropdown or by typing in the gene name and selecting it.
This page produces a UMAP or PCA plot that colours each cell by the average expression of a list of genes provided by the user. The list must be comma seperated but is case insensitive. Genes not present in the data will be ignored. Click visualize to see the plot.
This page will produce a table of candidate marker genes that may differentiate the clusters or cell types being compared. When 'Compare' is different to 'With' the table will be generated.