Single Cell Identificator Based on E-test (SciBet) is a computational tool for predicts cell identity for any randomly sequenced cell by single cell RNA sequencing technique. Based on oure unfied expression entropy model for scRNA-seq data, 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 and ~20,000 genes with only 1-core computer. We provide a binary package in R language including not only SciBet for classification, but also the expression entropy model for unsupervised and supervsed feature selection (E-test). Please see Installation section for 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.

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.