ms_psig: Determines which phenotypes are statistically significant

In aya49/flowGraph: Identifying differential cell populations in flow cytometry data accounting for marker frequency

Determines which phenotypes are statistically significant

Description

Determines which phenotypes are statistically significant based on SpecEnr.

Usage

ms_psig(
  ms_,
  summary_pars,
  summary_adjust,
  test_cust,
  test_custom,
  lyrno,
  mp_,
  me_
)

Arguments

ms_	sample x phenotype SpecEnr matrix
summary_pars	See flowGraphSubset.
summary_adjust	See flowGraphSubset.
test_cust	Final significance test function.
test_custom	Raw significance test function.
lyrno	An integer indicating total number of layers in the cell hierarchy including layer 0.
mp_	sample x phenotype proportion matrix.
me_	sample x phenotype expected proportion matrix.

Value

A logical vector the same length as the number of columns in ms_ indicating whether or not each phenotype is significant; used only for the fast version of flowGraph to determine whether or not to keep testing the phenotypes' children.

aya49/flowGraph documentation built on Feb. 4, 2024, 6:40 p.m.