clusterExperiment and RSEC: A Bioconductor package and framework for clustering of single-cell and other large gene expression datasets
Davide Risso, Liam Purvis, Russell Fletcher, Diya Das, John Ngai, Sandrine Dudoit, and Elizabeth Purdom. (2018). clusterExperiment and RSEC: A Bioconductor package and framework for clustering of single-cell and other large gene expression datasets. BioRxiv 280545.
Clustering of genes and/or samples is a common task in gene expression analysis. With the increasing popularity of single-cell transcriptome sequencing, many experiments are creating large gene expression datasets with the goal of detecting previously unknown heterogeneity within cells. It is common in the detection of novel subtypes to run many clustering algorithms, as well as rely on subsampling and ensemble methods to improve robustness. We introduce a Bioconductor R package, clusterExperiment, that implements a general and flexible strategy we entitle Resampling-based Sequential Ensemble Clustering (RSEC). Read more