The scPharm Online Analysis Platform is primarily designed to enable online access and computation of scPharm, which facilitates users to parse the pharmacological response of tumor samples to aid drug therapy and research. scPharm is a computational framework that integrates pharmacological profiles with scRNA-seq data to identify pharmacological subpopulations of cells within a tumor. It uses GSEA to assess the distribution of cell identity genes in drug response-determined gene lists, leveraging the correlation between NES and drug response at single-cell resolution. scPharm successfully identified sensitive subpopulations in breast cancer tissues, revealed dynamic changes in resistant subpopulations of lung cancer cells, and expanded to a mouse model. The framework also provides insights into combination drug strategies and evaluates drug toxicity in healthy cells within the tumor microenvironment. In addition, we implemented an immunotherapy recommendation analysis function using a combination of CM-drugs, Tres and TIDE metrics.
1. What can we do? Calculate the response of tumor samples to drugs, identify drug-sensitive and drug-resistant cell populations, recommend optimal therapeutic drugs, recommend combination drug strategies, analyze potential drug side effects, and recommend immunotherapy or not.
2. About input. scPharm is mainly targeted at tumor cell prediction, so the input needs to be single-cell sequencing data from tumor cell lines or tumor samples. For the input format, we encourage the use of data objects from your current Seurat analysis (uploaded in rds format), in addition to h5 files and expression matrices (genes x cells).
3. On parameters. Detailed parameters can be found in our GitHub repository with a detailed description of the parameters. Except for the mandatory and optional analysis parameters, default values can be used for all other parameters. Basic analysis includes single drug prediction if you enter any drug. Full analysis includes Dr_analysis, Comb_analysis and Dse_analysis corresponding to drug recommendation analysis, drug combination analysis, and drug side effect analysis, respectively. scPharm contains two modes, single drug mode and combo drug mode. The combo-drug mode enables predictive ranking of recommended combo-drugs based on existing real combo-drug treat data (gdsc-combination).
4. Access to results. We will allocate computing resources for analysis at the first time after submitting the analysis task, and send you a notification email as soon as the analysis is finished. So please be sure to submit a valid email address. A task id will be returned for every task submission, this is a unique identification number, please remember it if possible. You can also use your email to check all the tasks you have submitted if you forget. In the visualization page, your results can be accessed by searching task id or task name, and we provide a rich graphical display to present your results. All analyzed images, tables and files can be downloaded as a package or one by one on the download page.
5. What needs attention. Your analysis will only be retained for 1 week, due to storage resource limitations. In addition, for privacy and security reasons, the platform does not have a login system, so please do not disclose your task id. Please get your analysis results in time.
6. Cite us. P. Tian, J. Zheng, K. Qiao, Y. Fan, Y. Xu, T. Wu, S. Chen, Y. Zhang, B. Zhang, C. Ambrogio, H. Wang, scPharm: Identifying Pharmacological Subpopulations of Single Cells for Precision Medicine in Cancers. Adv. Sci. 2024, 2412419. https://doi.org/10.1002/advs.202412419 Endonote cite file
If you have any questions, please feel free to contact us. Suggestions and bug reports are welcome.
E-mail: [email protected]
Tel: 021-65980233
Address: No. 1239, Siping Road, Yangpu Area, Shanghai, China