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

SCANPY ： 大规模单细胞基因表达数据分析。

• 发表时间: 02 2018 6
• 来源期刊: Genome Biol
• DOI: 10.1186/s13059-017-1382-0
• PMID: 29409532
• 文章类型: Journal Article
• 作者列表: Wolf FA,Angerer P,Theis FJ

关键词: Bioinformatics; Clustering; Differential expression testing; Graph analysis; Machine learning; Pseudotemporal ordering; Scalability; Single-cell transcriptomics; Trajectory inference; Visualization

Mesh: Gene Expression Profiling / methods; Gene Regulatory Networks; Single-Cell Analysis; Software

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 ).