RNA-Seq

Transcriptome

Consensus clustering

Bioconductor

Biology

Correlation clustering

Gene

Data mining

Gene expression

Artificial intelligence

Computer science

Computational biology

Cluster analysis

CURE data clustering algorithm

Genetics

Robustness (evolution)

Nature Methods

Single-cell consensus clustering (SC3) provides user-friendly, robust and accurate cell clustering as well as downstream analysis for single-cell RNA-seq data. Single-cell RNA-seq enables the quantitative characterization of cell types based on global transcriptome profiles. We present single-cell consensus clustering (SC3), a user-friendly tool for unsupervised clustering, which achieves high accuracy and robustness by combining multiple clustering solutions through a consensus approach (                http://bioconductor.org/packages/SC3                              ). We demonstrate that SC3 is capable of identifying subclones from the transcriptomes of neoplastic cells collected from patients.

SC3: consensus clustering of single-cell RNA-seq data