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

> 商业许可源文 · EUROPE_PMC · [CC-BY](https://creativecommons.org/licenses/by/)

书目信息

引用：Wolf FA, Angerer P, Theis FJ. (2018). SCANPY: large-scale single-cell gene expression data analysis. Genome biology. PMID 29409532 · PMC5802054 · DOI 10.1186/s13059-017-1382-0

证据类型：PRIMARY_RESEARCH

主题：single-cell

被引次数（采集时）：6590

原始记录：[Europe PMC](https://europepmc.org/article/MED/29409532)

来源许可：[CC-BY](https://creativecommons.org/licenses/by/)

作者摘要（按来源许可复用）

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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