overLapper {systemPipeR} | R Documentation

## Set Intersect and Venn Diagram Functions

### Description

Function for computing Venn intersects or standard intersects among large numbers of label sets provided as `list` of `vectors`. The resulting intersect objects can be used for plotting 2-5 way Venn diagrams or intersect bar plots using the functions `vennPlot` or `olBarplot`, respectively. The `overLapper` function scales to 2-20 or more label vectors for Venn intersect calculations and to much larger sample numbers for standard intersects. The different intersect types are explained below under the definition of the `type` argument. The upper Venn limit around 20 label sets is unavoidable because the complexity of Venn intersects increases exponentially with the label set number `n` according to this relationship: `2^n - 1`. The current implementation of the plotting function `vennPlot` supports Venn diagrams for 2-5 label sets. To visually analyze larger numbers of label sets, a variety of intersect methods are introduced in the `olBarplot` help file. These methods are much more scalable than Venn diagrams, but lack their restrictive intersect logic.

### Usage

    overLapper(setlist, complexity = "default", sep = "_", cleanup = FALSE, keepdups = FALSE, type)

### Arguments

`setlist` | Object of class `list` where each list component stores a label set as `vector` and the name of each label set is stored in the name slot of each list component. The names are used for naming the label sets in all downstream analysis steps and plots.
`complexity` | Complexity level of intersects specified as integer vector. For Venn intersects it needs to be assigned `1:length(setlist)` (default). If `complexity=2` the function returns all pairwise intersects.
`sep` | Character used to separate set labels.
`cleanup` | If set to `TRUE` then all characters of the label sets are set to upper case, and leading and trailing spaces are removed. The default `cleanup=FALSE` omits this step.
`keepdups` | By default all duplicates are removed from the label sets. The setting `keepdups=TRUE` will retain duplicates by appending a counter to each entry.
`type` | With the default setting `type="vennsets"` the overLapper function computes the typical Venn intersects for the label sets provided under `setlist`. With the setting `type="intersects"` the function will compute pairwise intersects (not compatible with Venn diagrams). Venn intersects follow the typical 'only in' intersect logic of Venn comparisons, such as: labels present only in set A, labels present only in the intersect of A & B, etc. Due to this restrictive intersect logic, the combined Venn sets contain no duplicates. In contrast to this, regular intersects follow this logic: labels present in the intersect of A & B, labels present in the intersect of A & B & C, etc. This approach results usually in many duplications of labels among the intersect sets.

### Details

Additional Venn diagram resources are provided by the packages `limma`, `gplots`, `vennerable`, `eVenn` and `VennDiagram`, or online resources such as shapes, Venn Diagram Generator and Venny.

### Value

`overLapper` returns standard intersect and Venn intersect results as `INTERSECTset` or `VENNset` objects, respectively. These S4 objects contain the following components:

`setlist` | Original label sets accessible with `setlist()`.
`intersectmatrix` | Present-absent matrix accessible with `intersectmatrix()`, where each overlap set in the `vennlist` data component is labeled according to the label set names provided under `setlist`. For instance, the composite name 'ABC' indicates that the entries are restricted to A, B and C. The seperator used for naming the intersect sets can be specified under the `sep` argument.
`complexitylevels` | Complexity levels accessible with `complexitylevels()`.
`vennlist` | Venn intersects for `VENNset` objects accessible with `vennlist()`.
`intersectlist` | Standard intersects for `INTERSECTset` objects accessible with `intersectlist()`.

### Note

The functions provided here are an extension of the Venn diagram resources on this site: http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual#TOC-Venn-Diagrams

### Author(s)

Thomas Girke

### References

See examples in 'The Electronic Journal of Combinatorics': http://www.combinatorics.org/files/Surveys/ds5/VennSymmExamples.html

### See Also

`vennPlot`, `olBarplot`

### Examples

    ## Sample data
    setlist <- list(A=sample(letters, 18), B=sample(letters, 16),
                    C=sample(letters, 20), D=sample(letters, 22),
                    E=sample(letters, 18), F=sample(letters, 22))

    ## 2-way Venn diagram
    vennset <- overLapper(setlist[1:2], type="vennsets")
    vennPlot(vennset)

    ## 3-way Venn diagram
    vennset <- overLapper(setlist[1:3], type="vennsets")
    vennPlot(vennset)

    ## 4-way Venn diagram
    vennset <- overLapper(setlist[1:4], type="vennsets")
    vennPlot(list(vennset, vennset))

    ## Pseudo 4-way Venn diagram with circles
    vennPlot(vennset, type="circle")

    ## 5-way Venn diagram
    vennset <- overLapper(setlist[1:5], type="vennsets")
    vennPlot(vennset)

    ## Alternative Venn count input to vennPlot (not recommended!)
    counts <- sapply(vennlist(vennset), length)
    vennPlot(counts)

    ## 6-way Venn comparison as bar plot
    vennset <- overLapper(setlist[1:6], type="vennsets")
    olBarplot(vennset, mincount=1)

    ## Bar plot of standard intersect counts
    interset <- overLapper(setlist, type="intersects")
    olBarplot(interset, mincount=1)

    ## Accessor methods for VENNset/INTERSECTset objects
    names(vennset)
    names(interset)
    setlist(vennset)
    intersectmatrix(vennset)
    complexitylevels(vennset)
    vennlist(vennset)
    intersectlist(interset)

    ## Coerce VENNset/INTERSECTset object to list
    as.list(vennset)
    as.list(interset)

    ## Pairwise intersect matrix and heatmap
    olMA <- sapply(names(setlist),
    		function(x) sapply(names(setlist),
    		function(y) sum(setlist[[x]] %in% setlist[[y]])))
    olMA
    heatmap(olMA, Rowv=NA, Colv=NA)

    ## Presence-absence matrices for large numbers of sample sets
    interset <- overLapper(setlist=setlist, type="intersects", complexity=2)
    (paMA <- intersectmatrix(interset))
    heatmap(paMA, Rowv=NA, Colv=NA, col=c("white", "gray"))

[Package systemPipeR version 2.0.8 Index]