sig.var: Discover high discriminant genes in unsupervised manner

In charliex210/sctools: Tools for single cell RNAseq analysis

Description

Calculate statistical significance of variables driving latent variation using jackstraw

Usage

sig.var(mat, r = NULL, s = 100, B = 400, adj.method = "fdr",
  log = TRUE, scale = TRUE, verbose = FALSE, ...)

Arguments

mat	Gene expression matrix, columns are cells and rows are genes.
r	A number (a positive integer) of significant principal components.
s	A number (a positive integer) of “synthetic” null variables. Out of m variables, s variables are independently permuted.
B	A number (a positive integer) of resampling iterations. There will be a total of s*B null statistics.
adj.method	Correction method for p-values, see p.adjust.
log	Comppute PCA of logarithm.
scale	Scale the gene expression.
verbose	A logical specifying to print the computational progress.
...	Additional arguments passed on to jackstraw_pca.

Value

Statistical results of jackstraw.

charliex210/sctools documentation built on Dec. 29, 2021, 11:19 p.m.