Prefered/supported version of R is 3.5.3.
Use this command to install OmicsON package:
install.packages("BiocManager")
install.packages("devtools")
BiocManager::install(pkgs = c("STRINGdb", "BiocCheck", "mygene"))
Sys.setenv(R_REMOTES_NO_ERRORS_FROM_WARNINGS=TRUE)
devtools::install_github(repo = "cmujzbit/OmicsON", dependencies = TRUE, force = TRUE)
Short analysis example:
OmicsON::setUpReactomeMapping(
ChEBI2ReactomeFileURL = "https://reactome.org/download/current/ChEBI2Reactome.txt",
Ensembl2ReactomeFileURL = "https://reactome.org/download/current/Ensembl2Reactome.txt",
UniProt2ReactomeFileURL = "https://reactome.org/download/current/UniProt2Reactome.txt")
pathToFileWithLipidomicsData <- system.file(package = "OmicsON", "extdata", "nm-lipidomics.txt")
lipidomicsInputData <- read.table(pathToFileWithLipidomicsData, header = TRUE)
pathToFileWithTranscriptomicsData <- system.file(package = "OmicsON", "extdata", "nm-transcriptomics.txt")
transcriptomicsInputData <- read.table(pathToFileWithTranscriptomicsData, header = TRUE)
XDataFrame <- transcriptomicsInputData
YDataFrame <- lipidomicsInputData
xNamesVector <- as.character(transcriptomicsInputData$symbol)
yNamesVector <- as.character(lipidomicsInputData$ChEBI)
CcaResultsNoExtention <- OmicsON::makeCanonicalCorrelationAnalysis(
xNamesVector = xNamesVector,
yNamesVector = yNamesVector,
XDataFrame = XDataFrame,
YDataFrame = YDataFrame,
xCutoff = 0.6, yCutoff = 0.7)
OmicsON::plotCanonicalCorrelationAnalysisResults(
ccaResults = CcaResultsNoExtention,
main = "Structural Correlations (Transcriptomics vs Lipidomics)",
thirdLineText = "")
PlsResultsNoExtention <- OmicsON::makePartialLeastSquaresRegression(
xNamesVector = xNamesVector,
yNamesVector = yNamesVector,
XDataFrame = XDataFrame,
YDataFrame = YDataFrame)
OmicsON::plotRmsepForPLS(
PLSResult = PlsResultsNoExtention,
nCols = 3, nRows = 2, lty = c(2))
lipidomicsInputDataDecoratedByReactome <- OmicsON::decorateByReactomeData(
chebiMoleculesDf = lipidomicsInputData,
chebiIdsColumnName = "ChEBI",
organismTaxonomyId = '9606')
ontology2GenesSymboleFromEnsembleFunctionalInteractions <- OmicsON::createFunctionalInteractionsDataFrame(
chebiToReactomeDataFrame = lipidomicsInputDataDecoratedByReactome,
singleIdColumnName = 'ontologyId',
idsListColumnName = 'genesSymbolsFromEnsemble')
xNamesVector <- as.character(ontology2GenesSymboleFromEnsembleFunctionalInteractions$genesSymbolsFromEnsemble)
yNamesVector <- as.character(ontology2GenesSymboleFromEnsembleFunctionalInteractions$root)
XDataFrame <- transcriptomicsInputData
YDataFrame <- lipidomicsInputData
CcaResultsReactomeEnsembleExtentionOldData <- OmicsON::makeCanonicalCorrelationAnalysis(
xNamesVector = xNamesVector,
yNamesVector = yNamesVector,
XDataFrame = XDataFrame,
YDataFrame = YDataFrame,
xCutoff = 0.6, yCutoff = 0.7)
OmicsON::plotCanonicalCorrelationAnalysisResults(
ccaResults = CcaResultsReactomeEnsembleExtentionOldData,
main = "Structural Correlations (Transcriptomics vs Lipidomics)",
thirdLineText = "Reactome")
PlsResultsReactomeEnsembleExtentionOldData <- OmicsON::makePartialLeastSquaresRegression(
xNamesVector = xNamesVector,
yNamesVector = yNamesVector,
XDataFrame = XDataFrame,
YDataFrame = YDataFrame
)
OmicsON::plotRmsepForPLS(
PLSResult = PlsResultsReactomeEnsembleExtentionOldData,
nCols = 3, nRows = 2, lty = c(2))