SciBet as a portable and fast single cell type identifier
Chenwei Li, Baolin Liu, Boxi Kang, Zedao Liu, Yedan Liu, Changya Chen, Xianwen Ren, Zemin Zhang
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 supervised cell type identifier that accurately predicts cell identity for newly sequenced cells with order-of-magnitude speed advantage. We enable web client deployment of SciBet for rapid local computation without uploading local data to the server. Facing the exponential growth in the size of single cell RNA datasets, this user-friendly and cross-platform tool can be widely useful for single cell type identification.
Topics & Concepts
IdentifierComputer scienceUploadAnnotationIdentification (biology)Software deploymentComputationArtificial intelligenceWorld Wide WebComputer networkAlgorithmBiologyOperating systemBotanySingle-cell and spatial transcriptomicsCancer Genomics and DiagnosticsExtracellular vesicles in disease