easySCF: a tool for enhancing interoperability between R and Python for efficient single-cell data analysis
easySCF utilizes a unified data format (.h5 format) to facilitate data transfer between R and Python platforms. The tool has been evaluated for data processing speed, memory efficiency, and disk usage, as well as its capability to handle large-scale single-cell datasets. easySCF is available as an open-source package, with implementation details and documentation accessible at https://github.com/xleizi/easySCF.
Authors
- Guangyu Xu (ORCID: https://orcid.org/0000-0002-5272-1796)
- Lei Cui (ORCID: https://orcid.org/0000-0002-5238-1357)
- Yijun Shen (ORCID: https://orcid.org/0000-0002-7138-1221)
- Feng Jiang (ORCID: https://orcid.org/0000-0001-7042-3023)
- An Qin (ORCID: https://orcid.org/0000-0002-8785-8848)
- Wentao Zhang (ORCID: https://orcid.org/0000-0003-4087-7280)
- Haoyun Zhang (ORCID: https://orcid.org/0000-0002-8487-6506)
- Shuai Zhao
Institutions
- Guangxi Medical University (CN)
- Shanghai Jiao Tong University (CN)
- Shanghai Medical Information Center (CN)
- Shanghai CASB Biotechnology (China) (CN)
- Shanghai Ninth People's Hospital (CN)
Publication Details
- Journal
- Bioinformatics
- Published
- 2024-11-25
- DOI
- https://doi.org/10.1093/bioinformatics/btae710
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Shanghai Jiao Tong University
- School of Medicine, Shanghai Jiao Tong University