IsoGenem {IsoGene} | R Documentation |
The function calculates the values for the five test statistics (the global likelihood test, Williams, Marcus, M, and the modified M) for testing increasing and decreasing alternatives.
IsoGenem(x, y)
x |
indicates the dose levels |
y |
gene expression for all genes |
A list with components
E2.up |
the test statistic of global likelihood test for testing increasing alternative. |
Williams.up |
the test statistic of Williams for testing increasing alternative. |
Marcus.up |
the test statistic of Marcus for testing increasing alternative. |
M.up |
the M test statistic for testing increasing alternative. |
ModM.up |
the test statistic of the modified M for testing increasing alternative. |
E2.dn |
the test statistic of Williams for testing increasing alternative. |
Williams.dn |
the test statistic of global likelihood test for testing increasing alternative. |
Marcus.dn |
the test statistic of Williams for testing increasing alternative. |
M.dn |
the test statistic of global likelihood test for testing increasing alternative. |
ModM.dn |
the test statistic of Williams for testing increasing alternative. |
direction |
the direction with the higher likelihood of increasing (indicated by "u") or decreasing (indicated by "d") trend. |
This function calculates the five test statistics for both increasing and decreasing ordered alternatives for all the genes (rows in the data set).
Lin et al.
Testing for Trend in Dose-Response Microarray Experiments: a Comparison of Testing Procedures, Multiplicity, and Resampling-Based Inference, Lin et al. 2007, Stat. App. in Gen. & Mol. Bio., 6(1), article 26.
## Not run: set.seed(1234) x <- c(rep(1,3),rep(2,3),rep(3,3)) y1 <- matrix(rnorm(90, 1,1),10,9) # 10 genes with no trends y2 <- matrix(c(rnorm(30, 1,1), rnorm(30,2,1), rnorm(30,3,1)), 10, 9) # 10 genes with increasing trends y <- data.frame(rbind(y1, y2)) # y needs to be a data frame stat <- IsoGenem(x,y) stat ## End(Not run)