Seurat (version 1.2.1)

jackStraw: Determine statistical significance of PCA scores.

Description

Randomly permutes a subset of data, and calculates projected PCA scores for these 'random' genes. Then compares the PCA scores for the 'random' genes with the observed PCA scores to determine statistical signifance. End result is a p-value for each gene's association with each principal component.

Usage

jackStraw(object, num.pc = 30, num.replicate = 100, prop.freq = 0.01, do.print = FALSE)

Arguments

object

Seurat object

num.pc

Number of PCs to compute significance for

num.replicate

Number of replicate samplings to perform

prop.freq

Proportion of the data to randomly permute for each replicate

do.print

Print the number of replicates that have been processed.

Value

Returns a Seurat object where [e-mail] represents p-values for each gene in the PCA analysis. If project.pca is subsequently run, [e-mail] then represents p-values for all genes.

References

Inspired by Chung et al, Bioinformatics (2014)