scConsensus: combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data

scConsensus: combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data

Abstract Background Clustering is a crucial step in the analysis of single-cell data. Clusters identified in an unsupervised manner are typically annotated to cell types based on differentially expressed genes. In contrast, supervised methods use a reference panel of labelled transcriptomes to guide...

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Bibliographic Details
Main Authors: Bobby Ranjan, Florian Schmidt, Wenjie Sun, Jinyu Park, Mohammad Amin Honardoost, Joanna Tan, Nirmala Arul Rayan, Shyam Prabhakar
Format: Article
Language:English
Published: BMC 2021-04-01
Series:BMC Bioinformatics
Subjects:
ScRNA-seq
Clustering
Cell type annotation
Consensus method
Online Access:https://doi.org/10.1186/s12859-021-04028-4

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