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

SCANPY: large-scale single-cell gene expression data analysis.
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DOI:
10.1186/s13059-017-1382-0
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发表时间:
2018-02-06
期刊:
影响因子:
12.3
通讯作者:
Theis FJ
Theis FJ
中科院分区:
生物学1区
文献类型:
--
作者:
Wolf FA;Angerer P;Theis FJ

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Scanpy是一个可扩展的工具包,用于分析单细胞基因表达数据。它包括预处理,可视化,聚类,伪时间和轨迹推断,差异表达测试和基因调控网络模拟的方法。它基于Python的实现有效地处理了超过一百万个单元的数据集(https://github.com/theislab/Scanpy)。沿着Scanpy,我们介绍了AnnData,一个用于处理带注释的数据矩阵的通用类(https://github.com/theislab/anndata)。
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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