cumOverlap: Cumulative Overlap Analysis of Ordered Lists
In hdeberg/limma: Linear Models for Microarray Data

Description Usage Arguments Details Value Author(s) References Examples

Test whether the leading members of ordered lists significantly overlap.

1	cumOverlap(ol1, ol2)

`ol1`	vector containing first ordered list. Duplicate values not allowed.
`ol2`	vector containing second ordered list. Should contain the same values as found in `ol1` but in a possibly different order. Duplicate values not allowed.

The function compares the top n members of each list, for every possible n, and conducts an hypergeometric test for overlap. The function returns the value of n giving the smallest p-value.

The p-values are adjusted for multiple testing in a similar way to Bonferroni's method, but starting from the top of th e ranked list instead of from the smallest p-values. This approach is designed to be sensitive to contexts where the number of Ids involved in the significant overlap are a small proportion of the total.

The vectors ol1 and ol2 do not need to be of the same length, but only values in common between the two vectors will be used in the calculation.

This method was described in Chapter 4 of Wu (2011).

List containing the following components:

`n.total`	integer, total number of values in common between `ol1` and `ol2`.
`n.min`	integer, top table length leading to smallest adjusted p-value.
`p.min`	smallest adjusted p-value.
`n.overlap`	integer, number of overlapping IDs in first `n.min`.
`id.overlap`	vector giving the overlapping IDs in first `n.min`.
`p.value`	numeric, vector of p-values for each possible top table length.
`adj.p.value`	numeric, vector of Bonferroni adjusted p-values for each possible top table length.

Gordon Smyth and Di Wu

Wu, D (2011). Finding hidden relationships between gene expression profiles with application to breast cancer biology. PhD thesis, University of Melbourne. http://hdl.handle.net/11343/36278

GeneIds <- paste0("Gene",1:50)
ol1 <- GeneIds
ol2 <- c(sample(GeneIds[1:5]), sample(GeneIds[6:50]))
coa <- cumOverlap(ol1, ol2)
coa$p.min
coa$id.overlap