dataWurdinger {GRridge} | R Documentation |
The four objects are:
datWurdinger_BC: A matrix containing preprocessed mRNA sequencing data (quasi-gausian scale, normalized). Columns are samples (81 samples with Breast Cancer and Colorectal Cancer) and rows are features (18410 features).
respWurdinger: A factor containing responses for samples with Breast cancer (n=40) and colorectal cancer (n=41)
annotationWurdinger: A list containing ensembleID, geneSymbol, entrezID and chromosome location.;
coDataWurdinger: A list containing co-data sets from external sources, namely (i) a list of genes that are expressed in platelets; (ii) immunologic signature pathway and; (iii) transcription factor based pathway and a list of cancer somatic genes.
data(dataWurdinger)
This data is used for illustration in the application paper below.
Four R objects (see Description)
Wurdinger,T., et al (2015). RNA-seq of tumor-educated platelets enables blood-based pan-cancer, multiclass, and molecular pathway cancer diagnostics. Cancer Cell, 28(5), 666-676.
data(dataWurdinger) # Transform the data set to the square root scale dataSqrtWurdinger <- sqrt(datWurdinger_BC) # #Standardize the transformed data datStdWurdinger <- t(apply(dataSqrtWurdinger,1, function(x){(x-mean(x))/sd(x)})) # # A list of gene names in the primary RNAseq data genesWurdinger <- as.character(annotationWurdinger$geneSymbol)