article Open AccessTop 1% cited
SCANPY: large-scale single-cell gene expression data analysis
Genome biology · 2018 · Vol. 19(1) · pp. 15–15
F. Alexander Wolf✉(Helmholtz Zentrum München)Philipp Angerer(Helmholtz Zentrum München)Fabian J. Theis✉(Helmholtz Zentrum München)
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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References
The igraph software package for complex network research
Medical Entomology and Zoology · 2006 · 10,434 citations
Orchestrating high-throughput genomic analysis with Bioconductor
Nature Methods · 2015 · 3,927 citations
The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells
Nature Biotechnology · 2014 · 7,571 citations
Spatial reconstruction of single-cell gene expression data
Nature Biotechnology · 2015 · 7,447 citations
Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets
Cell · 2015 · 7,706 citations
MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data
Genome biology · 2015 · 3,474 citations
The Human Cell Atlas
eLife · 2017 · 2,286 citations
Reversed graph embedding resolves complex single-cell trajectories
Nature Methods · 2017 · 5,149 citations
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