Description Usage Arguments Value Note Author(s) References See Also Examples
The function obtains the list of significant genes using the SAM procedure for the five test statistics (the global likelihood test, Williams, Marcus, M, and the modified M).
1 | Isoqval(delta, allfdr, qqstat, stat)
|
delta |
the delta value as cut-off to find the number of significant genes |
allfdr |
the delta table obtained from function Isoallfdr |
qqstat |
output from function Isoqqstat containing the test statistics of permutations |
stat |
choose one of the five test statistics to use |
A list of components
res |
returns the list genes with descending q-values of the SAM procedure in three columns: the first column is the row number of the genes, the second column is the observed test statistic values, and the last column is the q-values |
sign.list |
returns the list of significant genes found by the defined delta value with descending p-values in three columns: the first column is the row number of the genes, the second column is the observed test statistic values, and the last column is the q-values |
This function obtains the list of significant genes 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.
Lin et al.
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.
isoreg
, Isoqqstat
,
Isoallfdr
, IsoTestSAM
, IsoSAMPlot
1 2 3 4 5 6 7 8 9 10 | 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")
qval <- Isoqval(delta=0.2, allfdr, qqstat, stat="E2")
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