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

Genome biology · 2018 · Vol. 19(1) · pp. 15–15
F. Alexander WolfPhilipp AngererFabian J. Theis

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 ).

Single-cell and spatial transcriptomicsGene expression and cancer classificationGene Regulatory Network AnalysisPython (programming language)PreprocessorInferenceVisualizationComputational biologyBiologyCluster analysisComputer scienceScalabilityData visualization

MeSH terms

SoftwareGene Expression ProfilingGene Regulatory NetworksSingle-Cell Analysis
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