outMap {OGSA} | R Documentation |
Creates PDF color map of where outliers occur coded for molecular type
outMap (outList, geneList, hmName = 'PatSpecMap.pdf', plotName = 'Outliers', truncGene = FALSE, clust=FALSE)
outList |
List with all outliers generated by outCallRank or outCallTib |
geneList |
Gene set to compare against |
hmName |
Name for PDF output file |
plotName |
Header for plot |
truncGene |
if TRUE, only include genes that have outlier in the plot, default is all genes in gene set |
clust |
If TRUE, clusters data and produces dendrograms |
A matrix used for generating heatmap
Ochs, M. F., Farrar, J. E., Considine, M., Wei, Y., Meshinchi, S., & Arceci, R. J. (n.d.). Outlier Analysis and Top Scoring Pair for Integrated Data Analysis and Biomarker Discovery. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 1-1. doi:10.1109/tcbb.2013.153
data(ExampleData) data('KEGG_BC_GS') # Set up Phenotype phenotype <- pheno names(phenotype) <- colnames(cnv) #set up datalist dataSet <- list(expr,meth,cnv) # set up values for expr-meth-cnv in that order tailLRL <- c('left', 'right', 'left') outTibLRL <- outCallTib(dataSet, phenotype=pheno, names=c('Expr', 'Meth', 'CNV'), tail=tailLRL) # put in your pathways here pdgfB <- pathGS$'BIOCARTA_PDGF_PATHWAY' outMap(outTibLRL, pdgfB, hmName='BC_PDGF_TIB.pdf', plotName='PDGF Outlier T-H LRL Calls')