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app.R
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## Single file app script
## Libraries ####
#
# if(!require(tidyverse)) install.packages("tidyverse", dependencies = TRUE)
# if(!require(BiocManager)) install.packages("BiocManager", dependencies = TRUE)
# options(repos = BiocManager::repositories())
# options("repos")
# if(!require(devtools)) install.packages("devtools")
# if(!require(WGCNA)) BiocManager::install("WGCNA")
# if(!require(shiny)) install.packages("shiny", dependencies = TRUE)
# if(!require(openxlsx)) install.packages("openxlsx", dependencies = TRUE)
# if(!require(pheatmap)) install.packages("pheatmap", dependencies = TRUE)
# if(!require(plotly)) install.packages("plotly", dependencies = TRUE)
# if(!require(shinythemes)) install.packages("shinythemes", dependencies = TRUE)
# if(!require(shinyWidgets)) install.packages("shinyWidgets", dependencies = TRUE)
# if(!require(gprofiler2)) install.packages("gprofiler2", dependencies = TRUE)
# if(!require(ggdendro)) install.packages("ggdendro", dependencies = TRUE)
# if(!require(withr)) install.packages("withr")
# if(!require(zip)) devtools::install_github("zip")
# if(!require(rmarkdown)) install.packages("rmarkdown")
library(BiocManager)
library(tidyverse)
library(shiny)
library(shinythemes)
library(shinyWidgets)
library(htmlwidgets)
library(openxlsx)
library(pheatmap)
library(plotly)
library(gprofiler2)
library(WGCNA)
library(withr)
library(zip)
library(rmarkdown)
library(ggdendro)
library(shiny)
library(ggpubr)
## Classes ####
### Classesx
## Classes not S4 need to be set as S4 classes using the setClass function: ####
setClass("hclust")
setClass("ggplot")
setClass("gg")
setClass("htmlwidget")
setClass("plotly")
setClass("pheatmap")
## setOldClass takes an S3 class and puts it into S4 compatible format
setOldClass("ggplot")
setOldClass("gg")
setOldClass(c("gg", "ggplot")) ## apparently you have to use setOldClass sequentially
## This language is incredibly stupid, no offense to Hadley
## Class WGCNA Parameters ####
setClass(Class = "WGCNAParameters",
slots = c(
power = "numeric",
networkType = "character",
replaceMissingAdjacencies = "logical",
TOMtype = "character",
minModuleSize = "numeric",
mergeCutHeight = "numeric",
pamRespectsDendro = "logical",
deepSplit = "numeric",
checkMissingData = "logical",
maxBlockSize = "numeric",
nPreclusteringCenters = "numeric",
verbose = "numeric"
))
## Class Raw Data ####
setClass(Class = "RawData",
slots = c(
path = "character",
data = "tbl_df",
NonDataColumns = "numeric"),
contains = class(tibble::tibble())
)
## Protein Dendrogram ####
setClass("ProteinDendrogram",
slots = c(
FileName = "character",
Plot = "ANY"
), contains = "recordedplot")
### Class Definition CleanData ####
setClass(Class = "CleanData",
slots = c(Data = "list",
NonDataColumns = "numeric",
Samples = "character",
Identifiers = "character"),
contains = class(tibble::tibble()))
## PairedComparisons(not in use yet) ####
## TODO: Implement statistical analysis into module eigenproteins analysis
setClass("PairedComparisons",
slots = c(
Comparisons = "list"
))
## Traits (not used yet) ####
### Class Definition Traits
### TODO: Implement traits analysis
setClass("Traits",
slots = c(
Traits_df = "list"
),
contains = "tbl_df")
BuildTraitsFromPath <- function(path){
traits_tib <- readr::read_csv(path)
traits_output <- new("Traits")
traits_output@Traits_df <- traits_tib
traits_output
}
## EigenproteinNetwork ####
setClass("EigenproteinNetwork",
slots = c(
FileName = "character",
Plot = "ANY"
), contains = "recordedplot")
### Class Definition ExperimentalGroups ####
setClass(Class = "ExperimentalGroups",
slots = c(
path = "character",
ExperimentalDataFrame = "list",
ExperimentalGroups = "character",
Sample = "character",
SignificanceTesting = "logical",
SigTestType = "character",
SigTestComparisons = "PairedComparisons"
))
## Class Definition UniprotDatabase ####
setClass("UniprotDatabase",
slots = c(
Path = "character",
Database = "tbl_df"
),
contains = class(tibble::tibble())
)
### Class Definition WGCNAHclust ####
setClass(Class = "WGCNAHclust",
slots = c(
hclust = "hclust"
)
)
## Class Definition WGCNAResults
setClass(Class = "WGCNAResults",
slots = c(
colors = "character",
unmergedColors = "character",
MEs = "list",
goodSamples = "logical",
goodGenes = "logical",
dendrogram = "WGCNAHclust",
TOMFiles = "character",
blockGenes = "list",
blocks = "numeric",
blocksOrder = "ANY",
MEsOK = "logical",
ExperimentalGroups = "character",
TOMatrix = "matrix"
),
contains = c("CleanData", class(tibble::tibble()))
)
### Class Definition ModuleEigenproteinsTidy ####
setClass("ModuleEigenproteinsTidy",
slots = c(
ModuleEigenproteins = "list"
), contains = "CleanData")
## Class Definition ModuleMembership ####
setClass("ModuleMembership",
slots = list(
Modules = "list"
),
contains = c(class(tibble::tibble()))
)
## gProfilerParameters2 ####
setClass("gProfilerParameters2",
slots = c(
organism = "character",
ordered_query = "logical",
multi_query = "logical",
significant = "logical",
exclude_iea = "logical",
measure_underrepresentation = "logical",
evcodes = "logical",
user_threshold = "numeric",
correction_method = "character",
domain_scope = "character",
custom_bg = "ANY",
numeric_ns = "character",
sources = "ANY",
as_short_link = "logical"
))
## GostPlotParameters ####
setClass("GostPlotParameters", slots = c(
capped = "logical",
interactive = "logical"
))
## EigenproteinHeatmap ####
setClass("EigenproteinHeatmap",
slots = c(
FileName = "character",
Plot = "pheatmap"
), contains = "pheatmap")
### Class Definition gProfilerResults ####
setClass("gProfilerResults",
slots = c(
Parameters = "gProfilerParameters2",
EnrichmentResults = "list"
),
contains = c(class(tibble::tibble()))
)
### Class Definition gProfilerPlot ####
setClass("gProfilerPlot",
slots = c(
Parameters = "GostPlotParameters",
Plot = "plotly"),
contains = class(plotly::plotly_empty()))
### Class Definition GostPlotCollection ####
setClass("GostPlotCollection",
slots = c(
Plots = "list",
Names = "character"
),
contains = class(plotly::plotly_empty()))
### Class Definition gProfilerResults ####
setClass("gProfilerResults",
slots = c(
Parameters = "gProfilerParameters2",
EnrichmentResults = "list"
),
contains = c(class(tibble::tibble()))
)
### Class Definition SampleClustering ####
setClass("SampleClustering",
slots = c(
FileName = "character",
Plot = "ggplot"
), contains = "ggplot")
### PowerDeterminationParameters Class ####
setClass("PowerDeterminationParameters",
slots = c(
R_squared_cutoff = "numeric",
powerVector = "numeric",
networkType = "character",
moreNetworkConcepts = "logical",
UserDefinedPower = "logical",
OverridePower = "numeric",
AutomaticPowerSelection = "logical"
))
### Class Definition ScaleFreeTopology ####
setClass("ScaleFreeTopology",
slots = c(
FileName = "character",
Plot = "ANY",
Parameters = "PowerDeterminationParameters",
powerEstimate = "numeric",
fitIndices = "list"
), contains = "recordedplot")
### Class Definition Eigenpr
### Class Definition ModuleEigenproteinDiagnostics ####
setClass("ModuleEigenproteinDiagnostics",
slots = c(
FileName = "character",
CorrDendrogram = "ANY",
AdjacencyHeatmap = "ANY",
CorrHeatmap = "ANY"
), contains = "recordedplot")
### Class Definition ModuleEigenproteinPlots ####
setClass("ModuleEigenproteinPlots",
slots = c(
Violin = "list",
Boxplot = "list",
Density = "list",
Names = "character"
), contains = "ggplot")
## TOMPlot ####
setClass("TOMPlot",
slots = c(
FileName = "character",
Plot = "recordedplot"
))
### Class Definition PlotsOutput ####
setClass("PlotsOutput",
slots = c(
PathToOutput = "character",
gProfilerPlots = "GostPlotCollection",
SampleClustering = "SampleClustering",
EigenproteinNetwork = "EigenproteinNetwork",
ProteinDendrogram = "ProteinDendrogram",
EigenproteinDiagnostics = "ModuleEigenproteinDiagnostics",
ModuleEigenproteinPlots = "ModuleEigenproteinPlots",
TOMPlot = "TOMPlot",
SFTPlot = "ScaleFreeTopology",
EigenproteinHeatmap = "EigenproteinHeatmap"
))
### Class Definition DataOutput ####
setClass("DataOutput",
slots = c(
VarianceExplained = "tbl_df",
ModuleEigenproteinsTidy = "tbl_df",
ModuleEigenproteinsWide = "tbl_df",
ModuleMembership = "list",
TOMatrix = "matrix",
gProfilerResults = "list"
))
## Class ServerOutput ####
setClass("ServerOutput",
slots = c(
Plots = "PlotsOutput",
Data = "DataOutput"
))
setClassUnion("missingOrNULL", c("missing", "NULL"))
#setOldClass(Classes = c("gg", "ggplot"))
setClassUnion("characterOrNULL", c("character", "missing", "NULL"))
setClassUnion("GostPlotCollectionOrNULL", c("GostPlotCollection","missingOrNULL"))
setClassUnion("SampleClusteringOrNULL", c("SampleClustering","missing","NULL"))
setClassUnion("ProteinClusteringOrNULL", c("ProteinDendrogram","missing","NULL"))
setClassUnion("ModuleEigenproteinDiagnosticsOrNULL",
c("ModuleEigenproteinDiagnostics","missing","NULL"))
setClassUnion("ModuleEigenproteinPlotsOrNULL",
c("ModuleEigenproteinPlots","missing","NULL"))
setClassUnion("ComparisonsOrNULL", c("missing", "NULL", "PairedComparisons"))
## Functions ####
## Functions
#
# plotSampleClusteringDendro <- function(dendro, fontSize = 15,
# fileName = "SampleClustering.pdf"){
# ggdendro::ggdendrogram(dendro, rotate = TRUE) +
# ggplot2::ggtitle("Sample Clustering to Detect Outliers") +
# ggplot2::xlab("Sample") +
# ggplot2::ylab("Height") +
# ggplot2::coord_flip() +
# ggplot2::theme_bw(base_size = fontSize)
#
# ggplot2::ggsave(filename = fileName,
# path = "Results",
# plot = ggplot2::last_plot())
# }
## Class Constructor: WGCNAParameters ####
WGCNAParameters <- function(power,
networkType = "signed",
replaceMissingAdjacencies = TRUE,
TOMtype = "signed",
minModuleSize = 20,
mergeCutHeight = 0.25,
pamRespectsDendro = FALSE,
deepSplit = 2,
checkMissingData = TRUE,
maxBlockSize = 30000,
nPreclusteringCenters = 10,
verbose = 5){
if(!is.numeric(power)){
warning("power coerced to numeric")
power <- as.numeric(power)
}
if(!is.character(networkType) | !(networkType %in% c("signed", "unsigned"))){
stop("Invalid networkType parameter!")
}
if(!is.numeric(minModuleSize)){
warning("minModuleSize coerced to numeric")
minModuleSize <- as.numeric(minModuleSize)
}
if(!is.numeric(mergeCutHeight)){
warning("mergeCutHeight coerced to numeric")
mergeCutHeight <- as.numeric(mergeCutHeight)
}
new("WGCNAParameters",
power = power,
networkType = networkType,
replaceMissingAdjacencies = replaceMissingAdjacencies,
TOMtype = TOMtype,
minModuleSize = minModuleSize,
mergeCutHeight = mergeCutHeight,
pamRespectsDendro = pamRespectsDendro,
deepSplit = deepSplit,
checkMissingData = checkMissingData,
maxBlockSize = maxBlockSize,
nPreclusteringCenters = nPreclusteringCenters,
verbose = verbose)
}
## Class Constructor: WGCNA Parameters ####
RawData <- function(path, data = NULL, non_data_columns = NULL){
if(!is.character(path)) stop("No valid data path given")
data <- tibble::as_tibble(data)
non_data_columns <- as.double(non_data_columns)
new("RawData", path = path, data = data, NonDataColumns = non_data_columns)
}
## Class Constructor: PairedComparisons
BuildPairedComparisonsFromPath <- function(path){
comparisons_tibb <- readr::read_csv(path)
comp_output <- new("PairedComparisons")
comp_output@Comparisons <- lapply(
split(comparisons_tibb, seq(nrow(comparisons_tibb))), unlist)
comp_output
}
## Class Constructor: Traits ####
BuildTraitsFromPath <- function(path){
traits_tib <- readr::read_csv(path)
traits_output <- new("Traits")
traits_output@Traits_df <- traits_tib
traits_output
}
## Class Constructor: ExperimentalGroups ####
ExperimentalGroups <- function(path,
ExperimentalGroups = NA,
Sample = NA){
if(!is.character(path)) stop("No valid experimental path given")
new("ExperimentalGroups", path = path, ExperimentalGroups = NA, Sample = NA)
}
## Class Constructor: UniprotDatabase
CreateUniprotDatabase <- function(path){
UniprotDatabaseObject <- new("UniprotDatabase")
uploadedDatabase <- readr::read_tsv(path)
UniprotDatabaseObject@Database <- tibble::tibble(Accession = uploadedDatabase$Entry,
Gene = uploadedDatabase$`Gene names`,
Protein = uploadedDatabase$`Protein names`)
UniprotDatabaseObject
}
## Class Constructor: WGCNAHclust
WGCNAHclust <- function(results){
new("WGCNAHclust", hclust = results[[6]][[1]])
}
## WGCNAResults Constructor
WGCNAResults <- function(results, CleanData, ExperimentalGroups){
WGCNA_results_length <- length(results)
WGCNAResultsObject <- new("WGCNAResults",
Samples = CleanData@Samples,
Identifiers = CleanData@Identifiers,
ExperimentalGroups =
ExperimentalGroups@ExperimentalGroups)
WGCNAResultsObject@Data <- CleanData@Data
if(WGCNA_results_length == 10){
WGCNAResultsObject@colors = results[[1]]
WGCNAResultsObject@unmergedColors = results[[2]]
WGCNAResultsObject@MEs = results[[3]]
WGCNAResultsObject@goodSamples = results[[4]]
WGCNAResultsObject@goodGenes = results[[5]]
WGCNAResultsObject@dendrogram = WGCNAHclust(results)
WGCNAResultsObject@TOMFiles = ifelse(is.null(results[[7]]),
yes = "NA", no = results[[7]])
WGCNAResultsObject@blockGenes = results[[8]]
WGCNAResultsObject@blocks = results[[9]]
WGCNAResultsObject@MEsOK = results[[10]]
WGCNAResultsObject@blocksOrder = NA
}else if(WGCNA_results_length == 11){
WGCNAResultsObject@colors = results[[1]]
WGCNAResultsObject@unmergedColors = results[[2]]
WGCNAResultsObject@MEs = results[[3]]
WGCNAResultsObject@goodSamples = results[[4]]
WGCNAResultsObject@goodGenes = results[[5]]
WGCNAResultsObject@dendrogram = WGCNAHclust(results)
WGCNAResultsObject@TOMFiles = ifelse(is.null(results[[7]]),
yes = "NA", no = results[[7]])
WGCNAResultsObject@blockGenes = results[[8]]
WGCNAResultsObject@blocks = results[[9]]
WGCNAResultsObject@blocksOrder = results[[10]]
WGCNAResultsObject@ME = results[[11]]
}
WGCNAResultsObject
}
## Class Constructor: ModuleEigenproteinsTidy
ModuleEigenproteinsTidy <- function(WGCNAResults,
ExperimentalGroups){
ME_object <- new("ModuleEigenproteinsTidy")
BuildModuleEigenproteinsTidy(ME_object,
WGCNAResults = WGCNAResults,
ExperimentalGroups = ExperimentalGroups)
}
## Class Constructor: gProfilerParameters
gProfilerParameters2 <- function(organism,
OrderedQuery = FALSE,
MultiQuery = FALSE,
Significant = FALSE,
ExcludeIEA = FALSE,
MeasureUnderrepresentation = FALSE,
EvCodes = FALSE,
UserThreshold = 0.05,
CorrectionMethod = "g_SCS",
DomainScope = "annotated",
CustomBkg = NULL,
NumericNS = "",
Sources = NULL,
AsShortLink = FALSE){
new("gProfilerParameters2",
organism = organism,
ordered_query = OrderedQuery,
multi_query = MultiQuery,
significant = Significant,
exclude_iea = ExcludeIEA,
measure_underrepresentation = MeasureUnderrepresentation,
evcodes = EvCodes,
user_threshold = UserThreshold,
correction_method = CorrectionMethod,
domain_scope = DomainScope,
custom_bg = CustomBkg,
numeric_ns = NumericNS,
sources = Sources,
as_short_link = AsShortLink
)
}
## Class Constructor GostPlotParameters
GostPlotParameters <- function(capped = TRUE,
interactive = TRUE){
new("GostPlotParameters",
capped = capped,
interactive = interactive)
}
## Class Constructor PowerDeterminationParameters
PowerDeterminationParameters <- function(R_squared_cutoff,
powerVector,
networkType = "signed",
moreNetworkConcepts = FALSE,
UserDefinedPower = FALSE,
OverridePower = 12,
AutomaticPowerSelection = TRUE
){
new("PowerDeterminationParameters",
R_squared_cutoff = R_squared_cutoff,
powerVector = powerVector,
networkType = networkType,
moreNetworkConcepts = moreNetworkConcepts,
UserDefinedPower = UserDefinedPower,
OverridePower = OverridePower,
AutomaticPowerSelection = AutomaticPowerSelection)
}
## ModuleEigenprotein Plots ####
ModuleEigenproteinPlots <- function(METidy,
comparisonsObject){
MEPlotsOutput <- new("ModuleEigenproteinPlots")
MEnames <- unique(METidy@ModuleEigenproteins$Module)
bp_list <- BoxPlot_IndividualModule_by_Experiment(METidy,
comparisonsObject)
names(bp_list) <- MEnames
bp_list[["All"]] <- BoxPlot_ModuleFacetWrapped_by_Experiment(METidy,
comparisonsObject)
vp_list <- ViolinPlot_IndividualModule_by_Experiment(METidy,
comparisonsObject)
names(vp_list) <- MEnames
vp_list[["All"]] <- ViolinPlot_ModuleFacetWrapped_by_Experiment(METidy,
comparisonsObject)
dens_list <- DensityPlot_IndividualModule_by_Experiment(METidy)
names(dens_list) <- MEnames
dens_list[["All"]] <- DensityPlot_ModuleFacetWrapped_by_Experiment(METidy)
MEPlotsOutput@Violin <- vp_list
MEPlotsOutput@Boxplot <- bp_list
MEPlotsOutput@Density <- dens_list
MEPlotsOutput
}
## Generate FileNames:
## Generics ####
### S4 Generics
setGeneric("BuildAllPlots",
function(METidy,
WGCNAResults,
CleanData,
WGCNAParameters,
SFTObject,
GostplotParameters,
gProfilerResults,
comparisonsObject) standardGeneric("BuildAllPlots"))
## Accessors for ServerOutput Objects ####
setGeneric("fetch_gostplots",
function(plotsOutput) standardGeneric("fetch_gostplots"))
setGeneric("fetch_SampleClustering",
function(plotsOutput) standardGeneric("fetch_SampleClustering"))
setGeneric("fetch_ProteinDendrogram",
function(plotsOutput) standardGeneric("fetch_ProteinDendrogram"))
setGeneric("fetch_EigenproteinDiagnostics",
function(plotsOutput) standardGeneric("fetch_EigenproteinDiagnostics"))
setGeneric("fetch_ModuleEigenproteinPlots",
function(plotsOutput) standardGeneric("fetch_ModuleEigenproteinPlots"))
setGeneric("fetch_TOMPlot",
function(plotsOutput) standardGeneric("fetch_TOMPlot"))
setGeneric("fetch_SFTPlot",
function(plotsOutput) standardGeneric("fetch_SFTPlot"))
setGeneric("fetch_MEPlots_names",
function(x) standardGeneric("fetch_MEPlots_names"))
setGeneric("fetch_gProfiler_names",
function(x) standardGeneric("fetch_gProfiler_names"))
setGeneric("transpose_tibble",
function(x, var, val) standardGeneric("transpose_tibble"))
setGeneric("fetch_MEplot_by_index",
function(ServerOutput, PlotType, index)
standardGeneric("fetch_MEplot_by_index"))
setGeneric("fetch_ME_violin", function(ServerOutput) standardGeneric("fetch_ME_violin"))
setGeneric("fetch_ME_boxplot", function(ServerOutput) standardGeneric("fetch_ME_boxplot"))
setGeneric("fetch_ME_density", function(ServerOutput) standardGeneric("fetch_ME_density"))
setGeneric("fetch_MEplot_by_index", function(ggplot_list) standardGeneric("fetch_MEplot_by_index"))
setGeneric("fetch_violin_plots", function(MEPlots) standardGeneric("fetch_violin_plots"))
setGeneric("fetch_boxplots", function(MEPlots) standardGeneric("fetch_boxplots"))
setGeneric("fetch_density_plots", function(MEPlots) standardGeneric("fetch_density_plots"))
### get specific_MEPlot ####
setGeneric("get_specific_MEPlot",
function(parent, slot, plot_name)
standardGeneric("get_specific_MEPlot"))
### get_specific_gostplot ####
setGeneric("get_specific_gostplot",
function(parent, plot_name)
standardGeneric("get_specific_gostplot"))
## accessors used for get_specific_diagnostic_plot ####
setGeneric("fetch_Protein_Dendrogram", function(parent) standardGeneric("fetch_Protein_Dendrogram"))
setGeneric("fetch_correlation_dendrogram", function(parent) standardGeneric("fetch_correlation_dendrogram"))
setGeneric("fetch_adjacency_heatmap", function(parent) standardGeneric("fetch_adjacency_heatmap"))
setGeneric("fetch_correlation_heatmap", function(parent) standardGeneric("fetch_correlation_heatmap"))
setGeneric("fetch_Eigenprotein_heatmap", function(parent) standardGeneric("fetch_Eigenprotein_heatmap"))
setGeneric("fetch_SFT_plot", function(parent) standardGeneric("fetch_SFT_plot"))
setGeneric("fetch_TOM_plot", function(parent) standardGeneric("fetch_TOM_plot"))
setGeneric("fetch_SampleClustering_dendro", function(parent) standardGeneric("fetch_SampleClustering_dendro"))
setGeneric("get_specific_diagnostic_plot", function(parent, plot) standardGeneric("get_specific_diagnostic_plot"))
## Transpose tibble ####
setGeneric("transpose_tibble",
function(x, var, val) standardGeneric("transpose_tibble"))
## Find_non_data_column_indexes ####
setGeneric("find_nondata_column_indexes",
function(object) standardGeneric("find_nondata_column_indexes"))
## ReadDataFromPath ####
setGeneric("ReadDataFromPath",
function(object) standardGeneric("ReadDataFromPath"))
## RawData object accessors ####
setGeneric("path", function(x) standardGeneric("path"))
setGeneric("path<-", function(x, value) standardGeneric("path<-"))
setGeneric("data", function(x) standardGeneric("data"))
setGeneric("data<-", function(x, value) standardGeneric("data<-"))
setGeneric("NonDataColumns", function(x) standardGeneric("NonDataColumns"))
setGeneric("NonDataColumns<-", function(x, value) standardGeneric("NonDataColumns<-"))
## CleanData object accessors ####
setGeneric("Data",
function(x) standardGeneric("Data"))
setGeneric("Data<-",
function(x, value) standardGeneric("Data<-"))
setGeneric("Samples", function(x) standardGeneric("Samples"))
setGeneric("Identifiers<-", function(x, value) standardGeneric("Identifiers<-"))
setGeneric("Identifiers", function(x) standardGeneric("Identifiers"))
setGeneric("Samples<-", function(x, value) standardGeneric("Samples<-"))
setGeneric("Samples", function(x) standardGeneric("Samples"))
## BuildCleanDataFromRaw ####
setGeneric("BuildCleanDataFromRawData",
function(x,y, ...) standardGeneric("BuildCleanDataFromRawData"))
## RunBlockwiseModules ####
setGeneric("RunBlockwiseModules",
function(parameters, cleaned_data){
standardGeneric("RunBlockwiseModules")
})
## BuildExperimentalGroupsFromPath ####
setGeneric("BuildExperimentalGroupsFromPath",
function(x) standardGeneric("BuildExperimentalGroupsFromPath"))
## plot for WGCNAHClust ####
setGeneric("plot")
## plotDendroAndColors ####
setGeneric("plotDendroAndColors",
function(dendro, colors, ...) standardGeneric("plotDendroAndColors"))
## BuildModuleEigenproteinsTidy ####
setGeneric("BuildModuleEigenproteinsTidy",
function(ModuleEigenproteinsTidy,
WGCNAResults,
ExperimentalGroups)
standardGeneric("BuildModuleEigenproteinsTidy"))
## BuildModuleMembership ####
setGeneric("BuildModuleMembership",
function(ModuleMembershipObject,
WGCNAResultsObject,
UniprotDatabaseObject,
RawDataObject) standardGeneric("BuildModuleMembership"))
## RunGProfilerEnrichment ####
setGeneric("RunGProfilerEnrichment",
function(ModuleMembershipObject,
gProfilerParametersObject, ...) standardGeneric("RunGProfilerEnrichment"))
## gost ####
setGeneric("gost", function(gProfilerParameters, ModuleMembership) standardGeneric("gost"))
## gostplot ####
setGeneric("gostplot", function(GostPlotParameters,
gProfilerResults) standardGeneric("gostplot"))
## gostplot ####
setGeneric("gostplot", function(GostPlotParameters,
gProfilerResults) standardGeneric("gostplot"))
## plotSamleClusteringDendro ####
setGeneric("plotSampleClusteringDendro",
function(CleanData) standardGeneric("plotSampleClusteringDendro"))
## PickSoftThreshold ####
setGeneric("PickSoftThreshold", function(PowerObject,
CleanData){standardGeneric("PickSoftThreshold")})
## ScaleFreeTopologyPlot ####
setGeneric("ScaleFreeTopologyPlot",
function(SFTObject) standardGeneric("ScaleFreeTopologyPlot"))
## plotEigenproteinNetwork####
setGeneric("plotEigenproteinNetwork", function(Results) standardGeneric("plotEigenproteinNetwork"))
## PlotProteinDendrogram ####
setGeneric("PlotProteinDendrogram", function(Results) standardGeneric("PlotProteinDendrogram"))
## PlotEigenproteinHeatmap ####
setGeneric("PlotEigenproteinHeatmap",
function(WGCNAResults) standardGeneric("PlotEigenproteinHeatmap"))
## PlotModuleEigenproteinDiagnostics ####
setGeneric("PlotModuleEigenproteinDiagnostics",
function(WGCNAResults) standardGeneric("PlotModuleEigenproteinDiagnostics"))
## ModuleEigenprotein Plotting generics ####
## Facet Wrapped
setGeneric("BoxPlot_ModuleFacetWrapped_by_Experiment",
function(METidy, comparisons) standardGeneric("BoxPlot_ModuleFacetWrapped_by_Experiment"))
setGeneric("ViolinPlot_ModuleFacetWrapped_by_Experiment",
function(METidy, comparisons) standardGeneric("ViolinPlot_ModuleFacetWrapped_by_Experiment"))
setGeneric("DensityPlot_ModuleFacetWrapped_by_Experiment",
function(METidy) standardGeneric("DensityPlot_ModuleFacetWrapped_by_Experiment"))
## By Module
setGeneric("BoxPlot_IndividualModule_by_Experiment",
function(METidy, comparisons)
standardGeneric("BoxPlot_IndividualModule_by_Experiment"))
setGeneric("ViolinPlot_IndividualModule_by_Experiment",
function(METidy, comparisons)
standardGeneric("ViolinPlot_IndividualModule_by_Experiment"))
setGeneric("DensityPlot_IndividualModule_by_Experiment",
function(METidy, comparisons)
standardGeneric("DensityPlot_IndividualModule_by_Experiment"))
## CreatePlotsOutput ####
setGeneric("CreatePlotsOutput", function(PathToOutput,
gProfilerPlots,
SampleClustering,
ProteinDendrogram,
EigenproteinDiagnostics,
ModuleEigenproteinPlots,
TOMPlot,
SFTPlot,
EigenproteinHeatmap) standardGeneric("CreatePlotsOutput"))
## Accessors for BuildDataOutput ####
setGeneric("BuildDataOutput", function(METidy,
WGCNAResults,
gProfiler,
CleanData,
MM_object) standardGeneric("BuildDataOutput"))
setGeneric("fetch_MEs_wide", function(WGCNAResults) standardGeneric("fetch_MEs_wide"))
setGeneric("fetch_MEs_tidy", function(METidy) standardGeneric("fetch_MEs_tidy"))
setGeneric("fetch_gProfiler_results", function(gProfilerResults) standardGeneric("fetch_gProfiler_results"))
setGeneric("fetch_gProfiler_parameters", function(gProfilerResults) standardGeneric("fetch_gProfiler_parameters"))
setGeneric("fetch_Module_Membership", function(MM_object) standardGeneric("fetch_Module_Membership"))
setGeneric("calc_prop_var", function(WGCNAResults, CleanData) standardGeneric("calc_prop_var"))
## plotTOM ####
setGeneric("plotTOM",
function(CleanData, WGCNAResults, WGCNAParameters) standardGeneric("plotTOM"))
## PropVarExplained ####
setGeneric("PropVarExplained",
function(CleanData, WGCNAResults) standardGeneric("PropVarExplained"))
## CreateServerOutput ####
setGeneric("CreateServerOutput",
function(PlotsOutput, DataOutput)
standardGeneric("CreateServerOutput"))
setGeneric("fetch_specific_gProfiler_result",
function(parent, plot_name) standardGeneric("fetch_specific_gProfiler_result"))
## PlotProteinDendrogram ####
setGeneric("PlotProteinDendrogram", function(Results) standardGeneric("PlotProteinDendrogram"))
setGeneric("plotEigenproteinNetwork", function(Results) standardGeneric("plotEigenproteinNetwork"))
setGeneric("PlotEigenproteinHeatmap",
function(WGCNAResults) standardGeneric("PlotEigenproteinHeatmap"))
## GenerateFileNames ####
setGeneric("GenerateFileNames", function(ServerOutput, temp_dir) standardGeneric("GenerateFileNames"))
setGeneric("WritePlots", function(ServerOutput, list_of_paths) standardGeneric("WritePlots"))
setMethod("WritePlots", signature("ServerOutput", "list"),
function(ServerOutput, list_of_paths){
## gProfilerPlots
gost_plots <- fetch_gostplots(ServerOutput)
withr::with_dir(new = dirname(list_of_paths[[1]][1]),
code = for(i in 1:length(gost_plots)){
htmlwidgets::saveWidget(gost_plots[[i]]@Plot,
file = list_of_paths[[1]][i],
selfcontained = TRUE)
})
violin_plots <- fetch_violin_plots(ServerOutput)
boxplots <- fetch_boxplots(ServerOutput)
density_plots <- fetch_density_plots(ServerOutput)
## Boxplots
for(i in 1:length(violin_plots)){
ggsave(filename = list_of_paths[[2]][i], plot = boxplots[[i]])
}
## Violin Plots
for(i in 1:length(violin_plots)){
ggsave(filename = list_of_paths[[3]][i], plot = violin_plots[[i]], device = "pdf")
}
## Density Plots
for(i in 1:length(violin_plots)){
ggsave(filename = list_of_paths[[4]][i], plot = density_plots[[i]], device = "pdf")
}
## Diagnostics
for(i in 1:3){
pdf(file = list_of_paths[[5]][i], width = 8, height = 6)
switch(i,
{replayPlot(fetch_correlation_dendrogram(ServerOutput))},
{replayPlot(fetch_adjacency_heatmap(ServerOutput))},
{replayPlot(fetch_correlation_heatmap(ServerOutput))})
dev.off()
}
## SFT Plot
pdf(file = list_of_paths[[6]], width = 8, height = 6)
replayPlot(fetch_SFT_plot(ServerOutput))
dev.off()
## Eigenprotein Heatmap
pdf(file = list_of_paths[[7]], width = 12, height = 9)
grid::grid.newpage()
grid::grid.draw(fetch_Eigenprotein_heatmap(ServerOutput)$gtable)
dev.off()
## TOMPlot
png(filename = list_of_paths[[8]],
width = 1200, height = 1200,
antialias = "none")
replayPlot(fetch_TOM_plot(ServerOutput))
dev.off()
})
## Methods ####
## GenerateFileNames ####
setMethod("GenerateFileNames", signature("ServerOutput", "character"),
function(ServerOutput, temp_dir){
## You can't have spaces in temporary directories !!!
gProfiler_names <- paste(file.path(temp_dir,
"gProfiler_Plots",
fetch_gProfiler_names(ServerOutput)),
".html",
sep = "")
MEPlots_names_boxplot <- file.path(temp_dir,
"Module_Eigenprotein_Plots",
"boxplots",
paste(fetch_MEPlots_names(ServerOutput),
"pdf",
sep = ".")
)
MEPlots_names_violin <- file.path(temp_dir,
"Module_Eigenprotein_Plots",
"violin",
paste(fetch_MEPlots_names(ServerOutput),
"pdf",
sep = ".")
)
MEPlots_names_density <- file.path(temp_dir,
"Module_Eigenprotein_Plots",
"density",
paste(fetch_MEPlots_names(ServerOutput),
"pdf",
sep = ".")
)
EPDiagnostics <- c("Correlation_Dendrogram",
"Adjacency_Heatmap",
"Correlation_Heatmap")
EP_Names <- file.path(temp_dir,
"Eigenprotein_Diagnostics",
paste(EPDiagnostics,
"pdf",
sep = "."))
SFT_names <- file.path(temp_dir, "Scale_Free_Topology_Plot.pdf")
EP_heatmap <- file.path(temp_dir, "Eigenprotein_Heatmap.pdf")
TOMPlot_names <- file.path(temp_dir, "TOMPlot.png")
list_of_paths <- list("gProfiler_paths" = gProfiler_names,
"MEPlots_paths_boxplot" = MEPlots_names_boxplot,
"MEPlots_paths_violin" = MEPlots_names_violin,
"MEPlots_paths_density" = MEPlots_names_density,
"EP_Names" = EP_Names,
"SFT_Names" = SFT_names,
"EP_heatmap" = EP_heatmap,
"TOMPlot_names" = TOMPlot_names)
return(list_of_paths)
})
## Generate DataFileNames ####
setGeneric("DataFileNames", function(ServerOutput, temp_dir) standardGeneric("DataFileNames"))
setMethod("DataFileNames", signature("ServerOutput", "character"),
function(ServerOutput, temp_dir){
csv_names <- c("Variance_Explained",
"ModuleEigenproteins_tidy",
"ModuleEigenproteinsWide")
excel_names <- c("WGCNAResults_Module_Membership",
"gProfiler_Enrichment_Results")
csv_filepaths <- file.path(temp_dir, paste(csv_names, "csv", sep = "."))
excel_filepaths <- file.path(temp_dir, paste(excel_names, ".xlsx", sep = "."))
list_of_paths <- list("variance_explained" = csv_filepaths[1],
"ME_tidy" = csv_filepaths[2],
"ME_wide" = csv_filepaths[3],
"WGCNAResults" = excel_filepaths[1],
"gProfiler" = excel_filepaths[2])
return(list_of_paths)
})
## WriteData ####
setGeneric("WriteData", function(ServerOutput, list_of_paths) standardGeneric("WriteData"))
setMethod("WriteData", signature("ServerOutput", "list"),
function(ServerOutput, list_of_paths){
## CSVs
write.csv(ServerOutput@Data@VarianceExplained, row.names = FALSE,
file = list_of_paths[[1]])
write.csv(ServerOutput@Data@ModuleEigenproteinsTidy,
file = list_of_paths[[2]])
write.csv(ServerOutput@Data@ModuleEigenproteinsWide,
file = list_of_paths[[3]])
## Excel sheets
## WGCNA Results
sheetNames <- names(ServerOutput@Data@ModuleMembership)
wb <- openxlsx::createWorkbook()
for(i in 1:length(sheetNames)) {
addWorksheet(wb, sheetNames[i])
writeData(wb,
sheetNames[i],
ServerOutput@Data@ModuleMembership[[i]],
withFilter = TRUE)