SciBet: An ultra-fast classifier for cell type identification using single cell RNA sequencing data

Li, C.; Liu, B.; Kang, B.; Liu, Z.; Liu, Y.; Ren, X.; Zhang, Z.

doi:10.1101/645358

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bioRxiv · 10.1101/645358

SciBet: An ultra-fast classifier for cell type identification using single cell RNA sequencing data

Li, C.·Liu, B.·Kang, B.·Liu, Z.·Liu, Y.·Ren, X.·Zhang, Z.

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Abstract

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.

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Li, C., Liu, B., Kang, B., Liu, Z., Liu, Y., Ren, X., Zhang, Z.. 2019-05-23. SciBet: An ultra-fast classifier for cell type identification using single cell RNA sequencing data. https://doi.org/10.1101/645358

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