SCANPY: large-scale single-cell gene expression data analysis

Genome Biology

F. Alexander Wolf¹  Philipp Angerer¹  Fabian J. Theis¹ 

[1] Helmholtz Zentrum München – German Research Center for Environmental Health, Institute of Computational Biology;

关键词: Single-cell transcriptomics;    Machine learning;    Scalability;    Graph analysis;    Clustering;    Pseudotemporal ordering;   

DOI  :  10.1186/s13059-017-1382-0

来源: DOAJ

【 摘 要 】

Abstract 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).

【 授权许可】

Unknown