SCANPY: large-scale single-cell gene expression data analysis
F. Alexander Wolf, Philipp Angerer, Fabian Joachim Theis
Helmholtz Munich Institute of Computational Biology Technical University of Munich
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摘要与影响
SCANPY is a scalable toolkit for analyzing single-cell gene expression data. It includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inference, differential expression testing, and simulation of gene regulatory networks. Its Python-based implementation efficiently deals with data sets of more than one million cells ( https://github.com/theislab/Scanpy ). Along with SCANPY, we present ANNDATA, a generic class for handling annotated data matrices ( https://github.com/theislab/anndata ).
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生物医学Single-cell and spatial transcriptomics
Gene expression and cancer classification · Gene Regulatory Network Analysis
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