pagoda.effective.cells: Estimate effective number of cells based on lambda1 of random...

In scde: Single Cell Differential Expression

Description

Examines the dependency between the amount of variance explained by the first principal component of a gene set and the number of genes in a gene set to determine the effective number of cells for the Tracy-Widom distribution

Usage

pagoda.effective.cells(pwpca, start = NULL)

Arguments

pwpca	result of the pagoda.pathway.wPCA() call with n.randomizations > 1
start	optional starting value for the optimization (if the NLS breaks, trying high starting values usually fixed the local gradient problem)

Value

effective number of cells

Examples

data(pollen)
cd <- clean.counts(pollen)

knn <- knn.error.models(cd, k=ncol(cd)/4, n.cores=10, min.count.threshold=2, min.nonfailed=5, max.model.plots=10)
varinfo <- pagoda.varnorm(knn, counts = cd, trim = 3/ncol(cd), max.adj.var = 5, n.cores = 1, plot = FALSE)
pwpca <- pagoda.pathway.wPCA(varinfo, go.env, n.components=1, n.cores=10, n.internal.shuffles=50)
pagoda.effective.cells(pwpca)

scde documentation built on Nov. 8, 2020, 6:19 p.m.