| runRankprod {EMA} | R Documentation |
Rank product method to identify differentially expressed genes. This method is useful for small samples size.
runRankprod(data, labels, q = 0.05, plot = TRUE)
data |
A matrix, a data frame, or an ExpressionSet object. Each row of 'data' (or 'exprs(data)', respectively) must correspond to a gene, and each column to a sample. |
labels |
A vector of integers corresponding to observation (column) class labels. For 2 classes, the labels must be 0 and 1. |
q |
A numeric value specifying the pvalue threshold. |
plot |
A logical value specifying if drawing plots or not. |
A list of two dataframes, the identification of up-regulated and down-regulated genes in class 2 compared to class 1, respectively. RP/Rsum : The rank product. AdjpValue : The adjusted pvalues. RawpValue : The raw pvalues. FC(class1/class2) : The fold change calculation.
EMA group
Breitling, R., Armengaud, P., Amtmann, A., and Herzyk, P.(2004) Rank Products: A simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments, FEBS Letter, 57383-92
## load data data(marty) ## Not run: ## filtering data marty <- expFilter(marty, threshold=3.5, graph=FALSE) ## End(Not run) ##Class label 0/1 marty.type.num <- ifelse(marty.type.cl=="Her2+",0,1) ## run differential analysis on example set example.subset <- marty[1:100,] out <- runRankprod(example.subset, labels=marty.type.num, q=0.05, plot=FALSE)