About SPEEDI
To facilitate single-cell omics analyses and improve reproducibility, we present SPEEDI, a fully automated end-to-end single-cell data science framework. SPEEDI introduces a data-driven batch inference method and transforms often heterogeneous data matrices obtained from different samples into a uniformly cell-type annotated and integrated dataset. By eliminating manual parameter selection, developing batch identification, providing full automation, and performing initial interpretive analyses, SPEEDI improves reproducibility and democratizes biological discovery using single-cell datasets.
This website allows users to upload their single cell datasets to our server for processing. Users can then view and download results once processing completes. To learn more about how to use this website, click the Help button above.
If you would like to install the SPEEDI R package on your own computer, please visit the SPEEDI GitHub repository. The SPEEDI vignette provides an overview of the package and a tutorial on how to process scRNA-seq data using SPEEDI.
The SPEEDI paper was published in Cell Systems on October 16, 2024.
Citation: Wang Y, Thistlethwaite W, Tadych A, Ruf-Zamojski F, Bernard DJ, Cappuccio A, Zaslavsky E, Chen X, Sealfon SC, Troyanskaya OG. Automated single-cell omics end-to-end framework with data-driven batch inference. Cell Systems. 2024 Oct 16;15(10):982-990.e5.
Run SPEEDI Analysis
To see an example of the results generated by SPEEDI, please visit the Example Results page. To confirm that your input data are in the correct format for processing, please visit the Help page.