sva.id: Surrogate Variable Analysis

Description Usage Arguments Value

View source: R/EigenMS.R

Description

Surrogate Variable Analysis function used internatlly by eig_norm1 and eig_norm2 Here we incorporate the model matrix from EigenMS normalization to find the significant trends in the matrix of residuals.

Usage

1
sva.id(dat, n.u.treatment, lm.fm, B = 500, sv.sig = 0.05)

Arguments

dat

number of peptides/genes x number of samples matrix of expression data with no missing values

n.u.treatment

number of treatment groups

lm.fm

formular for treatment to be use on the right side of the call to stats::lm() as generated by makeLMFormula()

B

The number of null iterations to perform

sv.sig

The significance cutoff for the surrogate variables

Value

A data structure with the following values:

n.sv

Number of significant surrogate variables

p.sv

Significance for the returned surrogate variables


ProteoMM documentation built on Nov. 8, 2020, 5:57 p.m.