Shaoxia
Shaoxia performs automated analysis of single-cell RNA sequencing (scRNA-seq) data to execute upstream processing, cell identity annotation, and downstream functional analysis.
Key Features:
- Analysis framework: Implements a three-stage workflow comprising upstream analysis, cell identity annotation, and downstream analysis.
- Automated workflows: Provides automated end-to-end processing of scRNA-seq datasets.
- High-performance computing: Utilizes high-performance computing to accelerate processing times.
- Comprehensive functionality: Offers functionality tailored for comprehensive interpretation of scRNA-seq data for functional genomics studies.
Scientific Applications:
- Cell-type identification: Enables cell identity annotation from scRNA-seq datasets.
- Single-cell transcriptomics: Facilitates interpretation of gene expression and cellular heterogeneity from scRNA-seq data.
- Functional genomics: Supports downstream analyses of scRNA-seq results for functional genomics investigations.
Methodology:
Performs automated upstream analysis, cell identity annotation, and downstream analysis for scRNA-seq data and employs high-performance computing to accelerate processing.
Topics
Details
- License:
- GPL-3.0
- Cost:
- Free of charge
- Tool Type:
- web application
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- Python, R, Shell
- Added:
- 7/18/2024
- Last Updated:
- 11/24/2024
Operations
Publications
Wei W, Xia X, Li T, Chen Q, Feng X. Shaoxia: a web-based interactive analysis platform for single cell RNA sequencing data. BMC Genomics. 2024;25(1). doi:10.1186/s12864-024-10322-1. PMID:38658838. PMCID:PMC11040744.
PMID: 38658838
PMCID: PMC11040744
Funding: - the National Natural Science Foundations of China: 82170971
- Fundamental Research Funds for the Central Universities: YJ201987
- Sichuan Science and Technology Program: 2021ZYD0090
- Scientific Research Foundation, West China Hospital of Stomatology Sichuan University: QDJF2019-3
- CAMS Innovation Fund for Medical Sciences: CIFMS 2019-I2M-5-004
Links
Repository
https://github.com/WiedenWei/shaoxia