PyLiger：用于 Python 的可扩展单细胞多组学数据集成。
PyLiger: scalable single-cell multi-omic data integration in Python.
机构信息
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Department of Computer Science and Engineering, University of Michigan, Ann Arbor, MI, USA.
出版信息
Bioinformatics. 2022 May 13;38(10):2946-2948. doi: 10.1093/bioinformatics/btac190.
MOTIVATION
LIGER (Linked Inference of Genomic Experimental Relationships) is a widely used R package for single-cell multi-omic data integration. However, many users prefer to analyze their single-cell datasets in Python, which offers an attractive syntax and highly optimized scientific computing libraries for increased efficiency.
RESULTS
We developed PyLiger, a Python package for integrating single-cell multi-omic datasets. PyLiger offers faster performance than the previous R implementation (2-5× speedup), interoperability with AnnData format, flexible on-disk or in-memory analysis capability and new functionality for gene ontology enrichment analysis. The on-disk capability enables analysis of arbitrarily large single-cell datasets using fixed memory.
AVAILABILITY AND IMPLEMENTATION
PyLiger is available on Github at https://github.com/welch-lab/pyliger and on the Python Package Index.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
动机
LIGER（Linked Inference of Genomic Experimental Relationships）是一个广泛使用的 R 包，用于单细胞多组学数据集成。然而，许多用户更喜欢在 Python 中分析他们的单细胞数据集，Python 提供了吸引人的语法和高度优化的科学计算库，以提高效率。
结果
我们开发了 PyLiger，这是一个用于整合单细胞多组学数据集的 Python 包。PyLiger 提供了比以前的 R 实现更快的性能（速度提高 2-5 倍），与 AnnData 格式的互操作性，灵活的磁盘或内存分析能力，以及新的用于基因本体富集分析的功能。磁盘上的功能使我们能够使用固定内存分析任意大的单细胞数据集。
可用性和实现
PyLiger 可在 Github 上的 https://github.com/welch-lab/pyliger 和 Python 包索引上获得。
补充信息
补充数据可在生物信息学在线获得。
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