Plots produced using the SAM procedure

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Description

The function produces four plots using the SAM procedure for one of the five test statistics (the likelihood ratio test, Williams, Marcus, the M and modified M tests): FDR vs. delta, number of significant genes vs. delta, number of false positives vs. delta, and the observed vs. expected SAM test statistics obtained from permutations.

Usage

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IsoSAMPlot(qqstat, allfdr, FDR, stat)

Arguments

qqstat

output from function Isoqqstat containing the test statistics of permutations

allfdr

the delta table obtained from function Isoallfdr

FDR

choose the desired FDR to control

stat

choose one of the five test statistics to use

Value

returns four plots produced using the SAM procedure.

Note

This function produces four plots using the SAM procedure for the five test statistics. To use the SAM procedure, the number of genes in the dataset is preferably larger than 500.

Author(s)

Lin et al.

References

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

Examples

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  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
  qqstat <- Isoqqstat(x, y, fudge="pooled", niter=50)
  allfdr <- Isoallfdr(qqstat, , stat = "E2")
  IsoSAMPlot(qqstat, allfdr, FDR = 0.1, stat = "E2")