Nothing
# Creates a new opossom environment
opossom.new <- function(preferences=NULL)
{
# Init the environment
env <- new.env()
env$color.palette.portraits <- NULL
env$color.palette.heatmaps <- NULL
env$t.ensID.m <- NULL
env$Fdr.g.m <- NULL
env$fdr.g.m <- NULL
env$files.name <- NULL
env$gene.info <- NULL
env$chromosome.list <- NULL
env$group.silhouette.coef <- NULL
env$group.colors <- NULL
env$group.labels <- NULL
env$gs.def.list <- NULL
env$samples.GSZ.scores <- NULL
env$spot.list.correlation <- NULL
env$spot.list.dmap <- NULL
env$spot.list.group.overexpression <- NULL
env$spot.list.kmeans <- NULL
env$spot.list.overexpression <- NULL
env$spot.list.samples <- NULL
env$spot.list.underexpression <- NULL
env$indata <- NULL
env$indata.gene.mean <- NULL
env$indata.sample.mean <- NULL
env$metadata <- NULL
env$n.0.m <- NULL
env$output.paths <- NULL
env$pat.labels <- NULL
env$p.g.m <- NULL
env$p.m <- NULL
env$perc.DE.m <- NULL
env$som.result <- NULL
env$t.g.m <- NULL
env$t.m <- NULL
env$groupwise.group.colors <- NULL
env$unique.protein.ids <- NULL
env$WAD.g.m <- NULL
env$csv.function <- write.csv2
# Generate some additional letters
env$LETTERS <- c(LETTERS, as.vector(sapply(1:10, function(x) {
return(paste(LETTERS, x, sep=""))
})))
env$letters <- c(letters, as.vector(sapply(1:10, function(x) {
return(paste(letters, x, sep=""))
})))
# Set default preferences
env$preferences <- list(dataset.name = "Unnamed",
note = "",
dim.1stLvlSom = "auto",
dim.2ndLvlSom = 20,
training.extension = 1,
rotate.SOM.portraits = 0,
flip.SOM.portraits = FALSE,
activated.modules = list( "reporting" = TRUE,
"primary.analysis" = TRUE,
"sample.similarity.analysis" = TRUE,
"geneset.analysis" = TRUE,
"geneset.analysis.exact" = FALSE,
"group.analysis" = TRUE,
"difference.analysis" = TRUE ),
database.biomart = "ENSEMBL_MART_ENSEMBL",
database.host = "jan2019.archive.ensembl.org",
database.dataset = "auto",
database.id.type = "",
standard.spot.modules = "dmap",
spot.coresize.modules = 3,
spot.threshold.modules = 0.95,
spot.coresize.groupmap = 5,
spot.threshold.groupmap = 0.75,
adjust.autogroup.number = 0,
feature.centralization = TRUE,
sample.quantile.normalization = TRUE,
pairwise.comparison.list = NULL)
# Merge user supplied information
if (!is.null(preferences))
{
env$preferences <-
modifyList(env$preferences, preferences[names(env$preferences)])
}
if(!is.null(preferences$indata))
{
env$indata <- preferences$indata
}
if(!is.null(preferences$group.labels))
{
env$group.labels <- preferences$group.labels
}
if(!is.null(preferences$group.colors))
{
env$group.colors <- preferences$group.colors
}
return(env)
}
# Executes the oposSOM pipeline.
opossom.run <- function(env)
{
util.info("Started:", env$preferences$started)
util.info("Name:", env$preferences$dataset.name)
#### Preparation & Calculation part ####
if (!util.call(pipeline.checkInputParameters, env)) {
return()
}
if(env$preferences$activated.modules$primary.analysis)
{
env$preferences$system.info <- Sys.info()
env$preferences$session.info <- sessionInfo()
env$preferences$started <- format(Sys.time(), "%a %d %b %Y %X")
}
if(env$preferences$activated.modules$reporting)
{
# create output dirs
dir.create(paste(env$files.name, "- Results"), showWarnings=FALSE)
dir.create(paste(env$files.name, "- Results/CSV Sheets"), showWarnings=FALSE)
if(env$preferences$activated.modules$primary.analysis)
{
util.call(pipeline.qualityCheck, env)
}
}
if(env$preferences$activated.modules$primary.analysis || env$preferences$activated.modules$geneset.analysis)
{
util.info("Loading gene annotation data.")
util.call(pipeline.prepareAnnotation, env)
}
if(env$preferences$activated.modules$primary.analysis)
{
util.info("Processing SOM. This may take several time until next notification.")
util.call(pipeline.prepareIndata, env)
util.call(pipeline.generateSOM, env)
filename <- paste(env$files.name, "pre.RData")
util.info("Saving environment image:", filename)
save(env, file=filename)
util.info("Processing Differential Expression Statistics")
util.call(pipeline.calcStatistics, env)
util.info("Detecting Spots")
util.call(pipeline.detectSpotsSamples, env)
util.call(pipeline.detectSpotsIntegral, env)
util.call(pipeline.patAssignment, env)
util.call(pipeline.groupAssignment, env)
}
if (env$preferences$activated.modules$geneset.analysis)
{
util.info("Calculating Geneset Enrichment")
util.call(pipeline.genesetStatisticSamples, env)
util.call(pipeline.genesetStatisticIntegral, env)
}
if(env$preferences$activated.modules$primary.analysis || env$preferences$activated.modules$geneset.analysis)
{
filename <- paste(env$files.name, ".RData", sep="")
util.info("Saving environment image:", filename)
save(env, file=filename)
if (file.exists(paste(env$files.name, "pre.RData")) && file.exists(filename))
{
file.remove(paste(env$files.name, "pre.RData"))
}
}
#### Reporting part ####
if(env$preferences$activated.modules$reporting)
{
util.info("Plotting Supporting Information")
util.call(pipeline.supportingMaps, env)
util.call(pipeline.entropyProfiles, env)
util.call(pipeline.topologyProfiles, env)
if(length(env$chromosome.list) > 0)
{
util.info("Plotting Chromosome Expression Reports")
util.call(pipeline.chromosomeExpressionReports, env)
}
if(ncol(env$indata) < 1000)
{
util.info("Plotting Sample Portraits")
util.call(pipeline.sampleExpressionPortraits, env)
}
if ( env$preferences$activated.modules$sample.similarity.analysis && ncol(env$indata) > 2)
{
util.info("Plotting Sample Similarity Analysis")
dir.create(file.path(paste(env$files.name, "- Results"), "Sample Similarity Analysis"), showWarnings=FALSE)
util.call(pipeline.sampleSimilarityAnalysisED, env)
util.call(pipeline.sampleSimilarityAnalysisCor, env)
util.call(pipeline.sampleSimilarityAnalysisICA, env)
util.call(pipeline.sampleSimilarityAnalysisSOM, env)
}
if (env$preferences$activated.modules$geneset.analysis)
{
dir.create(paste(env$files.name, "- Results/Geneset Analysis"), showWarnings=FALSE)
util.info("Plotting Geneset Enrichment Heatmaps")
util.call(pipeline.genesetOverviews, env)
util.info("Plotting Geneset Profiles and Maps")
util.call(pipeline.genesetProfilesAndMaps, env)
util.info("Calculating Cancer Hallmark Enrichment")
util.call(pipeline.cancerHallmarks, env)
}
util.info("Writing Gene Lists")
util.call(pipeline.geneLists, env)
util.info("Plotting Summary Sheets (Samples)")
util.call(pipeline.summarySheetsSamples, env)
util.info("Plotting Summary Sheets (Modules & PATs)")
util.call(pipeline.summarySheetsModules, env)
util.call(pipeline.summarySheetsPATs, env)
if(env$preferences$activated.modules$group.analysis && length(unique(env$group.labels)) >= 2)
{
util.info("Processing Group-centered Analyses")
util.call(pipeline.groupAnalysis, env)
}
if(env$preferences$activated.modules$difference.analysis)
{
util.info("Processing Difference Analyses")
util.call(pipeline.differenceAnalyses, env)
}
util.info("Generating HTML Report")
util.call(pipeline.htmlSampleSummary, env)
util.call(pipeline.htmlModuleSummary, env)
util.call(pipeline.htmlGenesetAnalysis, env)
util.call(pipeline.htmlSummary, env)
}
util.info("Finished:", format(Sys.time(), "%a %b %d %X"))
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.