scrat-package: Single Cell - R Analysis Toolbox

In hloefflerwirth/scrat: Single Cell - R Analysis Toolbox

Single Cell - R Analysis Toolbox

Description

This package translates single cell expression data into metadata of reduced dimension. It provides various sample-centered and group-centered visualizations, sample similarity analyses and pseudotime analysis. The underlying SOM algorithm combines feature clustering, multidimensional scaling and dimension reduction, along with strong visualization capabilities. It enables extraction and description of functional expression modules inherent in the data. The results are given within a separate folder and can be browsed using the summary HTML file.

Details

Package:	scrat
Type:	Package
Version:	2.1.0
Date:	2022-07-15
License:	GPL (>= 2)

Author(s)

Author: Henry Loeffler-Wirth <[e-mail]>, and Lena Richter

Maintainer: Henry Loeffler-Wirth <[e-mail]>

References

Loeffler-Wirth, Kalcher, Binder: oposSOM: R-package for high-dimensional portraying of genome-wide expression landscapes on Bioconductor. (Bioinformatics 2015)

Camp, G., Loeffler-Wirth, H. et al.: Multilineage communication regulates human liver bud development from pluripotency. (Nature 2017)

Examples

## Example with artificial data
env <- scrat.new(list(dataset.name="Example",
                        dim.1stLvlSom=10))

env$indata <- matrix(runif(10000), 1000, 10)

scrat.run(env)

hloefflerwirth/scrat documentation built on Sept. 2, 2022, 4:09 a.m.