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| Auteurs principaux: | , , , , , , , |
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| Format: | Artículo científico |
| Langue: | en |
| Publié: |
Bioinformatics (Oxford, England)
2024
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| Sujets: | |
| Accès en ligne: | https://pubmed.ncbi.nlm.nih.gov/39585309/ |
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| _version_ | 1868266277662883841 |
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| author | Zhang, Haoyun Zhang, Wentao Zhao, Shuai Xu, Guangyu Shen, Yi Jiang, Feng Qin, An Cui, Lei |
| author_facet | Zhang, Haoyun Zhang, Wentao Zhao, Shuai Xu, Guangyu Shen, Yi Jiang, Feng Qin, An Cui, Lei Zhang, Haoyun Zhang, Wentao Zhao, Shuai Xu, Guangyu Shen, Yi Jiang, Feng Qin, An Cui, Lei |
| collection | PubMed - marine biology |
| contents | easySCF: a tool for enhancing interoperability between R and Python for efficient single-cell data analysis. Zhang, Haoyun Zhang, Wentao Zhao, Shuai Xu, Guangyu Shen, Yi Jiang, Feng Qin, An Cui, Lei Software Single-Cell Analysis Computational Biology Programming Languages Humans This study introduces easySCF, a tool designed to enhance the interoperability of single-cell data between the two major bioinformatics platforms, R and Python. By supporting seamless data exchange, easySCF improves the efficiency and accuracy of 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. |
| format | Artículo científico |
| id | pubmed_39585309 |
| institution | PubMed |
| language | en |
| publishDate | 2024 |
| publisher | Bioinformatics (Oxford, England) |
| record_format | pubmed |
| spellingShingle | easySCF: a tool for enhancing interoperability between R and Python for efficient single-cell data analysis. Zhang, Haoyun Zhang, Wentao Zhao, Shuai Xu, Guangyu Shen, Yi Jiang, Feng Qin, An Cui, Lei Software Single-Cell Analysis Computational Biology Programming Languages Humans easySCF: a tool for enhancing interoperability between R and Python for efficient single-cell data analysis. Zhang, Haoyun Zhang, Wentao Zhao, Shuai Xu, Guangyu Shen, Yi Jiang, Feng Qin, An Cui, Lei Software Single-Cell Analysis Computational Biology Programming Languages Humans This study introduces easySCF, a tool designed to enhance the interoperability of single-cell data between the two major bioinformatics platforms, R and Python. By supporting seamless data exchange, easySCF improves the efficiency and accuracy of 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. |
| title | easySCF: a tool for enhancing interoperability between R and Python for efficient single-cell data analysis. |
| topic | Software Single-Cell Analysis Computational Biology Programming Languages Humans |
| url | https://pubmed.ncbi.nlm.nih.gov/39585309/ |