pagoda.show.pathways: View pathway or gene weighted PCA

In scde: Single Cell Differential Expression

Description

Takes in a list of pathways (or a list of genes), runs weighted PCA, optionally showing the result.

Usage

pagoda.show.pathways(pathways, varinfo, goenv = NULL, n.genes = 20,
  two.sided = FALSE, n.pc = rep(1, length(pathways)), colcols = NULL,
  zlim = NULL, showRowLabels = FALSE, cexCol = 1, cexRow = 1,
  nstarts = 10, cell.clustering = NULL, show.cell.dendrogram = TRUE,
  plot = TRUE, box = TRUE, trim = 0, return.details = FALSE, ...)

Arguments

pathways	character vector of pathway or gene names
varinfo	output of pagoda.varnorm()
goenv	environment mapping pathways to genes
n.genes	number of genes to show
two.sided	whether the set of shown genes should be split among highest and lowest loading (T) or if genes with highest absolute loading (F) should be shown
n.pc	optional integer vector giving the number of principal component to show for each listed pathway
colcols	optional column color matrix
zlim	optional z color limit
showRowLabels	controls whether row labels are shown in the plot
cexCol	column label size (cex)
cexRow	row label size (cex)
nstarts	number of random starts for the wPCA
cell.clustering	cell clustering
show.cell.dendrogram	whether cell dendrogram should be shown
plot	whether the plot should be shown
box	whether to draw a box around the plotted matrix
trim	optional Winsorization trim that should be applied
return.details	whether the function should return the matrix as well as full PCA info instead of just PC1 vector
...	additional arguments are passed to the c.view.pathways

Value

cell scores along the first principal component of shown genes (returned as invisible)

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