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

作者：F. Alexander Wolf, Philipp Angerer, Fabian J. Theis · 发表于：Genome biology · 年份：2018 · DOI：10.1186/s13059-017-1382-0 · 被引用次数：9826 · 研究领域：Single-cell and spatial transcriptomics、Gene expression and cancer classification、Gene Regulatory Network Analysis

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 ).