PT  - JOURNAL ARTICLE
AU  - Chenwei Li
AU  - Baolin Liu
AU  - Boxi Kang
AU  - Zedao Liu
AU  - Yedan Liu
AU  - Changya Chen
AU  - Xianwen Ren
AU  - Zemin Zhang
TI  - SciBet: a portable and fast single cell type identifier
AID  - 10.1101/645358
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 645358
4099  - http://biorxiv.org/content/early/2019/09/10/645358.short
4100  - http://biorxiv.org/content/early/2019/09/10/645358.full
AB  - Fast, robust and technology-independent computational methods are needed for supervised cell type annotation of single-cell RNA sequencing data. We present SciBet, a Bayesian 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.