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bioRxiv · 10.1101/174029

Scanpy for analysis of large-scale single-cell gene expression data

Wolf, F. A.·Angerer, P.·Theis, F. J.
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Abstract

We present Scanpy, a scalable toolkit for analyzing single-cell gene expression data. It includes preprocessing, visualization, clustering, pseudotime and trajectory inference, differential expression testing and simulation of gene regulatory networks. The Python-based implementation efficiently deals with datasets of more than one million cells and enables easy interfacing of advanced machine learning packages. Code is available from https://github.com/theislab/scanpy.

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Wolf, F. A., Angerer, P., Theis, F. J.. 2017-08-09. Scanpy for analysis of large-scale single-cell gene expression data. https://doi.org/10.1101/174029

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