plot_design: Plot model

In bhagwataditya/importomics: Unified Statistical Modeling of Omics Data

Plot model

Description

Plot model

Usage

plot_design(object, codingfun = contr.treatment.explicit)

Arguments

object

´SummarizedExperiment

codingfun

factor coding function contr.treatment: intercept = y0, coefi = yi - y0 contr.treatment.explicit: intercept = y0, coefi = yi - y0 code_control: intercept = ymean, coefi = yi - y0 contr.diff: intercept = y0, coefi = yi - y(i-1) code_diff: intercept = ymean, coefi = yi - y(i-1) code_diff_forward: intercept = ymean, coefi = yi - y(i+) code_deviation: intercept = ymean, coefi = yi - ymean (drop last) code_deviation_first: intercept = ymean, coefi = yi - ymean (drop first) code_helmert: intercept = ymean, coefi = yi - mean(y0:(yi-1)) code_helmert_forward: intercept = ymean, coefi = yi - mean(y(i+1):yp)

Value

ggplot

Examples

file <- system.file('extdata/billing19.proteingroups.txt', package = 'autonomics')
subgroups <- paste0(c('E00', 'E01', 'E02', 'E05', 'E15', 'E30', 'M00'), '_STD')
object <- read_maxquant_proteingroups(file, subgroups = subgroups)
object$subgroup %<>% substr(1,3)
plot_design(object)

bhagwataditya/importomics documentation built on Nov. 28, 2024, 8:28 a.m.