| runIndTest {EMA} | R Documentation |
This function computes test statistics, e.g., two-sample Welch t-statistics, t-statistics, or wilcoxon, independently for each row of a data frame.
runIndTest(data, labels, gene.names = NULL, plot = TRUE, dirname= NULL,
grp.name=c("Group1","Group2"))
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. |
gene.names |
A vector of description or name for each gene. |
plot |
A logical value specifying if drawing plots or not. |
dirname |
If specified, the .png plots are created in the directory. |
grp.name |
Vector with the name of the two groups |
For each gene independently, the function tests for the normality (Shapiro test) and the variance equality (F test) of each groups. According to the results, a welch test, a student test or a wilcoxon test is performed.
A matrix with the gene names, the statistics, and the p-values.
EMA group
shapiro.test, var.test,t.test,wilcox.test
## load data data(marty) ##random choice of genes - in practice genes of interest geneOfInterest<-sample(1:ncol(marty),5) ##Class label 0/1 marty.type.num <- ifelse(marty.type.cl=="Her2+",0,1) ## run differential analysis out <- runIndTest(marty[geneOfInterest,], labels=marty.type.num)