BestopCloud: an integrated one-stop solution for single-cell RNA sequencing data analysis
Single-cell RNA sequencing (scRNA-seq) technology has emerged as a powerful tool for unveiling cellular heterogeneity, yet the high dimensionality and complexity of the data it generates pose analytical challenges for non-professional programmers. To streamline the process, we have developed BestopCloud, a functionally comprehensive and user-friendly online analysis platform. Comprising nine modules, BestopCloud supports diverse parameter settings within each module and is capable of producing high-quality chart files. Furthermore, these modules can be used independently and flexibly linked through data flow. In summary, BestopCloud provides researchers with an in-depth solution for scRNA-seq data processing, analysis, and visualization.
Authors
- Tiantian Wang (ORCID: https://orcid.org/0000-0003-2958-8066)
- Rufei Pan
- Lian Cai (ORCID: https://orcid.org/0000-0002-1096-700X)
- Feifei Shi (ORCID: https://orcid.org/0000-0002-5375-8179)
- Panfei Wang
- Wenling Zheng (ORCID: https://orcid.org/0009-0001-4499-6650)
- Kyung Song (ORCID: https://orcid.org/0000-0002-9761-8733)
- Chao Li (ORCID: https://orcid.org/0000-0002-1950-0190)
- Jing Liu (ORCID: https://orcid.org/0000-0001-7309-0340)
- Jie Liu (ORCID: https://orcid.org/0000-0002-3849-6414)
- Haixia Wei
Institutions
- Beijing VDJBio (China) (CN)
- Beijing Founder Electronics (China) (CN)
- Building Engineering and Science Talent (US)
- Beijing Survey and Design Institute (China) (CN)
Publication Details
- Journal
- BMC Genomics
- Published
- 2025-10-09
- DOI
- https://doi.org/10.1186/s12864-025-12072-0
- Citations
- 1
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.81