Isofudge: Calculation of the fudge factor for the five SAM test...
In IsoGene: Order-Restricted Inference for Microarray Experiments

Description Usage Arguments Value Note Author(s) References See Also Examples

The function calculates the fudge factor for SAM test statistics for the five test statistics (the global likelihood test, Williams, Marcus, M, and the modified M).

1	Isofudge(x, y)

`x`	indicates the dose levels
`y`	gene expression for all genes

A vector of five fudge factor values for the five SAM test statistics.

This function calculates the fudge factor for SAM test statistics for the five test statistics.

Lin et al.

Modeling Dose-response Microarray Data in Early Drug Development Experiments Using R, Lin D., Shkedy Z., Yekutieli D., Amaratunga D., and Bijnens, L. (editors), (2012), Springer.

IsoGene: An R Package for Analyzing Dose-response Studies in Microarray Experiments, Pramana S., Lin D., Haldermans P., Shkedy Z., Verbeke T., De Bondt A., Talloen W., Goehlmann H., Bijnens L. 2010, R Journal 2/1.

isoreg, Isoallfdr, IsoGenemSAM, Isoqqstat, Isoqval,IsoTestSAM,IsoSAMPlot

  set.seed(1234)
  x <- c(rep(1,3),rep(2,3),rep(3,3))
  y1 <- matrix(rnorm(4500, 1,1),500,9) ## 500 genes with no trends
  y2 <- matrix(c(rnorm(1500, 1,1),rnorm(1500,2,1),
    rnorm(1500,3,1)),500,9) ## 500 genes with increasing trends
  y <- data.frame(rbind(y1, y2)) ##y needs to be a data frame
  fudge.factor <- Isofudge(x,y)