Methods

Data structure: anndata fields used for visualization

Expression data

Gene expression values are pulled from anndata.X. These feed into the histograms, scatterplot, colorscale, and differential expression calculations. We’re working on ways to incorporate anndata.raw and other anndata.layers!

Metadata

Categorical (e.g., cluster labels) and continuous (e.g., pseudotime) metadata are pulled from anndata.obs. Any column added here will be available for visualization in cellxgene. You can also create new categorical annotations within the application.

Embeddings

cellxgene looks for embeddings (e.g., tSNE, UMAP, PCA, spatial coordinates) in anndata.obsm. These fields must follow the scanpy convention of starting with X_, e.g., anndata.obsm['X_umap']. If an embedding has more than two components, the first two will be used for visualization.

Differential expression

We’re actively working on how to improve differential expression within the app.

Currently, we use a Welch’s t-test implementation, including the same variance overestimation correction as used in scanpy. We sort the tscore to identify the top 15 genes, and then filter to remove any that fall below a cutoff log fold change value, which can help remove spurious test results. The default threshold is 0.01 and can be changed using the option --diffexp-lfc-cutoff.