olink_lmer_plot: Function which performs a point-range plot per protein on a...

In OlinkAnalyze: Facilitate Analysis of Proteomic Data from Olink

Function which performs a point-range plot per protein on a linear mixed model

Description

Generates a point-range plot faceted by Assay using ggplot and ggplot2::geom_pointrange based on a linear mixed effects model using lmerTest:lmer and emmeans::emmeans. See olink_lmer for details of input notation.

Usage

olink_lmer_plot(
  df,
  variable,
  outcome = "NPX",
  random,
  olinkid_list = NULL,
  covariates = NULL,
  x_axis_variable,
  col_variable = NULL,
  number_of_proteins_per_plot = 6,
  verbose = FALSE,
  ...
)

Arguments

df	NPX data frame in long format with at least protein name (Assay), OlinkID, UniProt, 1-2 variables with at least 2 levels.
variable	Single character value or character array. Variable(s) to test. If length > 1, the included variable names will be used in crossed analyses . Also takes ':' or '*' notation.
outcome	Character. The dependent variable. Default: NPX.
random	Single character value or character array.
olinkid_list	Character vector indicating which proteins (by OlinkID) for which to create figures.
covariates	Single character value or character array. Default: NULL. Covariates to include. Takes ':' or '*' notation. Crossed analysis will not be inferred from main effects.
x_axis_variable	Character. Which main effect to use as x-axis in the plot.
col_variable	Character. If provided, the interaction effect col_variable:x_axis_variable will be plotted with x_axis_variable on the x-axis and col_variable as color.
number_of_proteins_per_plot	Number plots to include in the list of point-range plots. Defaults to 6 plots per figure
verbose	Boolean. Default: True. If information about removed samples, factor conversion and final model formula is to be printed to the console.
...	coloroption for color ordering

Value

A list of objects of class "ggplot" showing point-range plot of NPX (y-axis) over x_axis_variable for each assay (facet), colored by col_variable if provided.

Examples

library(dplyr)

lmer_results <- olink_lmer(df = npx_data1,
                           variable=c("Time", 'Treatment'),
                           random = c('Subject'))

assay_list <- lmer_results %>%
    filter(Threshold == 'Significant' & term == 'Time:Treatment') %>%
    select(OlinkID) %>%
    distinct() %>%
    pull()

list_of_pointrange_plots <- olink_lmer_plot(df = npx_data1,
                                            variable=c("Time", 'Treatment'),
                                            random = c('Subject'),
                                            x_axis_variable = 'Time',
                                            col_variable = 'Treatment',
                                            verbose=TRUE,
                                            olinkid_list = assay_list,
                                            number_of_proteins_per_plot = 10)

OlinkAnalyze documentation built on Nov. 4, 2023, 1:07 a.m.