CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data.

ABSTRACT:

Background

Single-cell RNA sequencing is fast becoming one the standard method for gene expression measurement, providing unique insights into cellular processes. A number of methods, based on general dimensionality reduction techniques, have been suggested to help infer and visualise the underlying structure of cell populations from single-cell expression levels, yet their models generally lack proper biological grounding and struggle at identifying complex differentiation paths.

Results

Here we introduce cellTree: an R/Bioconductor package that uses a novel statistical approach, based on document analysis techniques, to produce tree structures outlining the hierarchical relationship between single-cell samples, while identifying latent groups of genes that can provide biol

SUBMITTER: duVerle DA 

PROVIDER: S-EPMC5020541 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature