Gene Set Scoring on the Nearest Neighbor Graph (gssnng) for Single Cell RNA-seq (scRNA-seq)

Motivation Gene set scoring is a common task in bioinformatics, but the sparsity of data points in single cell gene expression creates difficulties. Results By applying matrix smoothing to the nearest neighbor graph of cells, high quality gene set scores can be produced on a per-cell level which is useful for visualization and statistical analysis. Importantly, within UMAP visualizations, the method preserves score-gradients across clusters of cells. Contact david.gibbs@isbscience.org Software gssnng is available on the python package index (PyPI). It can be installed using ‘pip install gssnng’. More information and demo notebook See https://github.com/gibbsdavidl/gssnng