Calculation of the fudge factor for the five SAM test statistics in the SAM procedure

Share:

Description

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).

Usage

1
  Isofudge(x, y)

Arguments

x

indicates the dose levels

y

gene expression for all genes

Value

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

Note

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

Author(s)

Lin et al.

References

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.

See Also

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

Examples

1
2
3
4
5
6
7
  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)