Seurat (version 2.1.0)

CalcVarExpRatio: Calculate the ratio of variance explained by ICA or PCA to CCA

Description

Calculate the ratio of variance explained by ICA or PCA to CCA

Usage

CalcVarExpRatio(object, reduction.type = "pca", grouping.var, dims.use)

Arguments

object

Seurat object

reduction.type

type of dimensional reduction to compare to CCA (pca, pcafast, ica)

grouping.var

variable to group by

dims.use

Vector of dimensions to project onto (default is the 1:number stored for cca)

Value

Returns Seurat object with ratio of variance explained stored in [e-mail]$var.ratio

Examples

# NOT RUN {
pbmc_small
# Requires CCA to have previously been run
# As CCA requires two datasets, we will split our test object into two just for this example
pbmc1 <- SubsetData(pbmc_small,cells.use = [e-mail][1:40])
pbmc2 <- SubsetData(pbmc_small,cells.use = [e-mail][41:80])
[e-mail]$group <- "group1"
[e-mail]$group <- "group2"
pbmc_cca <- RunCCA(pbmc1,pbmc2)
pbmc_cca <- CalcVarExpRatio(pbmc_cca,reduction.type = "pca", grouping.var = "group", dims.use = 1:5)

# }