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

Author:
Wolf, F. Alexander, Angerer, Philipp, Theis, Fabian J.
Source:
Genome biology 2018 v.19 no.1 pp. 15
ISSN:
1474-760X
Subject:
data collection, gene expression, gene expression regulation, gene regulatory networks
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).
Agid:
5898227