A portable and fast single cell type identifier
Fast, robust and technology-independent computational methods are needed for supervised cell type annotation of single-cell RNA sequencing data. We present SciBet, a single-cell classifier that accurately predicts cell identity for newly sequenced cells or cell clusters. We enable web client deployment of SciBet for rapid local computation without uploading local data to the server. This user-friendly and cross-platform tool can be widely useful for single cell type identification.
Installing dependency package
Before installing SciBet, the dependency packages should be installed first:
install.packages("Rcpp")
install.packages("RcppEigen")
install.packages("ggsci")
install.packages("viridis")
install.packages("tidyverse")
Installing SciBet
To install SciBet, run:
if (!requireNamespace("devtools", quietly = TRUE)) install.packages("devtools")
devtools::install_github("PaulingLiu/scibet")
For more details and basic usage see following tutorials:
The scripts for producing all the quantitative results in our manuscript can be found in scripts.
If you use SciBet in your research, please considering citing:
Please contact us:
Baolin Liu: pauling.liu@pku.edu.cn
Boxi Kang: chrisk@pku.edu.cn
Chenwei Li: lichenwei@pku.edu.cn
Zemin Zhang: zemin@pku.edu.cn
©2019 Chenwei Li, Baolin Liu, Boxi Kang. Zhang Lab. All rights reserved.