Single Cell Identificator Based on E-test (SciBet) is a computational tool for predicting cell identity for any randomly sequenced cell by single cell RNA sequencing technique. Compared to other supervised cell type identification methods, SciBet achieves adventages in accuracy, robustness, scalability and especially in speed. We can complete the analysis of accurate feature selection and classification in only around 1 second for a dataset including ~100,000 cells with an ordinary computer. We not only provide a binary package in R language, but also provide around 100 trained modes from multiple datasets. In addition, users can use SciBet online to upload their custom datasets for classification. Please see Installation section or Online Classification section for detailed instructions.

In our documention, we demostrate our R package by performing a series of comprehensive analysis for a recently published T-cell dataset. Please see Documention section for details.

A test version of SciBet implemented in pure R language is available, especially for Windows users who may sometimes have difficulties in installing R packages. See Installation section for details.

If you meet any questions, please do not hesitate to contact us for supporting. Please see Contact section for details, or join our Google user group.