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

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Detalles Bibliográficos
Autores principales: Wolf, F. Alexander, Angerer, Philipp, Theis, Fabian J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5802054/
https://www.ncbi.nlm.nih.gov/pubmed/29409532
http://dx.doi.org/10.1186/s13059-017-1382-0
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author Wolf, F. Alexander
Angerer, Philipp
Theis, Fabian J.
author_facet Wolf, F. Alexander
Angerer, Philipp
Theis, Fabian J.
author_sort Wolf, F. Alexander
collection PubMed
description 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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spelling pubmed-58020542018-02-14 SCANPY: large-scale single-cell gene expression data analysis Wolf, F. Alexander Angerer, Philipp Theis, Fabian J. Genome Biol Software 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). BioMed Central 2018-02-06 /pmc/articles/PMC5802054/ /pubmed/29409532 http://dx.doi.org/10.1186/s13059-017-1382-0 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Wolf, F. Alexander
Angerer, Philipp
Theis, Fabian J.
SCANPY: large-scale single-cell gene expression data analysis
title SCANPY: large-scale single-cell gene expression data analysis
title_full SCANPY: large-scale single-cell gene expression data analysis
title_fullStr SCANPY: large-scale single-cell gene expression data analysis
title_full_unstemmed SCANPY: large-scale single-cell gene expression data analysis
title_short SCANPY: large-scale single-cell gene expression data analysis
title_sort scanpy: large-scale single-cell gene expression data analysis
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5802054/
https://www.ncbi.nlm.nih.gov/pubmed/29409532
http://dx.doi.org/10.1186/s13059-017-1382-0
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