cellTree-package: Inference and visualisation of Single-Cell RNA-seq Data data...

In cellTree: Inference and visualisation of Single-Cell RNA-seq data as a hierarchical tree structure

Description

This packages computes a Latent Dirichlet Allocation (LDA) model of single-cell RNA-seq data and build a compact tree modelling the relationship between individual cells over time or space.

Details

A typical use-case will require you to run compute.lda on your expression data, to fit an LDA model, followed by compute.backbone.tree to generate a tree structure from the LDA model.

Plotting functions ct.plot.grouping and ct.plot.topics will then help you plot the tree structure with the desired annotations, while function cell.ordering.table will output an ordered table of cells, ranked by their position in the tree.

To get further information on each topic, you can run Gene Ontology enrichment tests, using compute.go.enrichment, plot the result tables as a graph using ct.plot.go.dag or render it with LaTeX, using go.results.to.latex.

cellTree documentation built on Nov. 8, 2020, 5:05 p.m.