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

Comparing the result of a global test performed on a subset to the test results of random subsets of the same size.

1 | ```
comparative(object, N = 1e3, z.scores = TRUE, trace)
``` |

`object` |
A |

`N` |
The number of random subsets to generate. |

`z.scores` |
If set to |

`trace` |
If set to |

In a situation when many covariates out of a large set are associated with the response, it is sometimes interesting to know p-value of the tested subset compares to random subsets of the same size. The `comparative`

function calculates the proportion of random subsets of the covariates of the same size as the tested subset that have a better score than the tested subset. This proportion is a diagnostic tool to help interpret the test result; it should not be interpreted as a p-value.

An object of class `gt.object`

with an appropriate column added to the test results matrix.

Jelle Goeman: j.j.goeman@lumc.nl; Jan Oosting

The comparative proportion is an enrichment type analysis. For the pros and cons of such an analysis, see

Goeman and Buhlmann (2007) Analyzing gene expression data in terms of gene sets: methodological issues. Bioinformatics 23 (8) 980-987.

The `gt`

function. The `gt.object`

function and useful functions associated with that object.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
# Simple examples with random data here
# Real data examples in the Vignette
# Random data: covariates A,B,C are correlated with Y
set.seed(1)
Y <- rnorm(20)
X <- matrix(rnorm(200), 20, 10)
X[,1:3] <- X[,1:3] + Y
colnames(X) <- LETTERS[1:10]
# Some subsets of interest
my.sets <- list(c("A", "B"), c("C","D"), c("D", "E"))
# Comparative proportions
res <- gt(Y, X, subsets = my.sets)
comparative(res)
comparative(res, z.scores=FALSE)
``` |

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