README.md

Ouija

Ouija is a probabilistic pseudotime framework. Ouija

Getting started

Installation

# install.packages("devtools")
devtools::install_github("kieranrcampbell/ouija")

To build the Ouija vignette install using

devtools::install_github("kieranrcampbell/ouija", local = FALSE, 
                          args = "--preclean", build_vignettes = TRUE)

Model fitting

Input is a cell-by-gene expression matrices that is non-negative and represents logged gene expression values. We recommend using log2(TPM + 1). This can either take the form of a matrix or a SingleCellExperiment (use of the SingleCellExperiment infrastructure is highly encouraged for single-cell analyses). By default the logcounts assay of a SingleCellExperiment will be used.

To fit the pseudotimes, pass the input data to the ouija function:

library(ouija)
data(example_gex) # synthetic gene expression data bundled
oui <- ouija(example_gex)
pseudotimes <- map_pseudotime(oui)

The map_pseudotimes function extracts the maximum-a-posteriori (MAP) estimates of the pseudotimes.

For further usage options see the vignette. A prebuilt vignette can be found here.

Authors

Kieran Campbell & Christopher Yau Wellcome Trust Centre for Human Genetics, University of Oxford

Artwork

Artwork by cwcyau, the mysterious banksy-esque artist of the statistical genomics world.



kieranrcampbell/bnlfa documentation built on Dec. 2, 2019, 12:44 p.m.