trelli_rnaseq_heatmap: Heatmap trelliscope building function for RNA-seq data

In pmartR/pmartRqc: Panomics Marketplace - Quality Control and Statistical Analysis for Panomics Data

Heatmap trelliscope building function for RNA-seq data

Description

Specify a plot design and cognostics for the RNA-seq heatmap trelliscope. Data must be grouped by an e_meta column. Main_effects order the y-variables. All statRes data is ignored. For MS/NMR data, use "trelli_abundance_heatmap".

Usage

trelli_rnaseq_heatmap(
  trelliData,
  cognostics = c("sample count", "mean LCPM", "biomolecule count"),
  ggplot_params = NULL,
  interactive = FALSE,
  path = .getDownloadsFolder(),
  name = "Trelliscope",
  test_mode = FALSE,
  test_example = 1,
  single_plot = FALSE,
  ...
)

Arguments

trelliData	A trelliscope data object made by as.trelliData, and grouped by an emeta variable. Must be built using seqData. Required.
cognostics	A vector of cognostic options. Defaults are "sample count", "mean LCPM" and "biomolecule count". "sample count" and "mean LCPM" are reported per group, and "biomolecule count" is the total number of biomolecules in the biomolecule class (e_meta column).
ggplot_params	An optional vector of strings of ggplot parameters to the backend ggplot function. For example, c("ylab(”)", "xlab(”)"). Default is NULL.
interactive	A logical argument indicating whether the plots should be interactive or not. Interactive plots are ggplots piped to ggplotly. Default is FALSE.
path	The base directory of the trelliscope application. Default is Downloads.
name	The name of the display. Default is Trelliscope
test_mode	A logical to return a smaller trelliscope to confirm plot and design. Default is FALSE.
test_example	A vector of plot indices to return for test_mode. Default is 1.
single_plot	A TRUE/FALSE to indicate whether 1 plot (not a trelliscope) should be returned. Default is FALSE.
...	Additional arguments to be passed on to the trelli builder

Value

No return value, builds a trelliscope display of heatmaps that is stored in 'path'

Author(s)

David Degnan, Lisa Bramer

Examples

## Not run: 
library(pmartRdata)

omicsData_seq <- group_designation(omicsData = rnaseq_object, main_effects = c("Virus"))

# Filter low transcript counts
omicsData_seq <- applyFilt(filter_object = total_count_filter(omicsData = omicsData_seq), 
 omicsData = omicsData_seq, min_count = 15)

# Select a normalization and statistics method (options are 'edgeR', 'DESeq2', and 'voom').
# See ?difexp_seq for more details
statRes_seq <- diffexp_seq(omicsData = omicsData_seq, method = "voom")

# Generate the trelliData object
trelliData_seq2 <- as.trelliData(omicsData = omicsData_seq)
trelliData_seq4 <- as.trelliData(omicsData = omicsData_seq, statRes = statRes_seq)

# Build the RNA-seq heatmap with an omicsData object with emeta variables. 
# Generate trelliData in as.trelliData.
trelli_panel_by(trelliData = trelliData_seq2, panel = "Gene") %>% 
   trelli_rnaseq_heatmap(test_mode = TRUE, test_example = c(1532, 1905, 6134), path = tempdir())
   
# Users can modify the plotting function with ggplot parameters and interactivity, 
# and can also select certain cognostics.     
trelli_panel_by(trelliData = trelliData_seq4, panel = "Gene") %>% 
   trelli_rnaseq_heatmap(test_mode = TRUE, test_example = c(1532, 1905, 6134), 
     ggplot_params = c("ylab('')", "xlab('')"), 
     interactive = TRUE, cognostics = c("biomolecule count"), path = tempdir())  

\dontshow{closeAllConnections()}

## End(Not run)

pmartR/pmartRqc documentation built on April 25, 2024, 6:18 a.m.