ISASweep {eisa} | R Documentation

## Create an ISA module tree

### Description

These functions create and plot the hierarchical description of an expression data set, by applying the ISA with various thresholds, and connecting the related modules. See details below.

### Usage

    ISASweep (expset, modules, ...)
    ISASweepGraph (sweep.result)
    ISASweepGraphPlot (graph, vertex.label=V(graph)$id,
      vertex.label.topleft=NA, vertex.label.topright=NA,
      vertex.label.bottomleft=NA, vertex.label.bottomright=NA,
      vertex.label.cex=0.8, edge.label=NA, asp=FALSE, rescale=FALSE,
      xlim=range(graph$layout[,1]), ylim=range(graph$layout[,2]),
      thresholds=TRUE, xlab=NA, ylab=NA, ...)

### Arguments

`expset` | The expression set object, if it is not an `ISAExpressionSet`, then `ISANormalize` is called on it.
`modules` | An `ISAModules` object.
`...` | Additional arguments. `ISASweep` passes these to `isa.sweep`; `ISASweepGraphPlot` passes additional arguments to `plot.igraph`.
`sweep.result` | An `ISAModules` object that contains the sweep tree information as well.
`graph` | An igraph graph object, the sweep tree.
`vertex.label` | Vertex labels, by default the ids of the modules.
`vertex.label.topleft` | Vertex labels to put at the top left corner.
`vertex.label.topright` | Vertex labels to put at the top right corner.
`vertex.label.bottomleft` | Vertex labels to put at the bottom left corner.
`vertex.label.bottomright` | Vertex labels to put at the bottom right corner.
`vertex.label.cex` | Magnification factor for the vertex labels.
`edge.label` | Edge labels.
`asp` | Logical scalar, whether the plot should have 1:1 aspect ratio.
`rescale` | Logical scalar, whether to rescale the layout coordinates to the [-1,1] interval.
`xlim` | Numeric vector of length two, the X limits of the plot.
`ylim` | Numeric vector of length two, the Y limits of the plot.
`thresholds` | Logical scalar, whether to add the (non-constant) thresholds to the plot.
`xlab` | The label of the horizontal axis, by default omitted.
`ylab` | The label of the vertical axis, by default omitted.

### Details

The ISA uses two threshold parameters that tune the sizes of the transcription modules. The sweep graph of an expression set is defined as the following. It is a directed graph, where the vertices are ISA modules, found at some threshold parameter values. There is an edge from module A to module B, if using 1) (the genes of) module A as the seed vector and 2) the threshold parameters used to find module B, the ISA converges to module B.

The `ISASweep` function creates an ISA sweep tree, in which one threshold parameter is kept fixed and the other varies. It starts from the modules found at the most stringent (=highest) threshold parameters, and uses them individually as seeds at the next less stringent threshold level. If this ISA iteration converges to an already known module, then an edge of the sweep tree is found. If the iteration converges to a new module, then this is added to the module list, together with the sweep tree edge. Then we proceed with the next level of modules, towards the less stringent threshold parameters.

The `ISASweepGraph` function creates a graph object that corresponds to the sweep tree of the expression set.

The `ISASweepGraphPlot` function plots a graph created with `ISASweepGraph`.

### Value

`ISASweep` returns an `ISAModules` object, with some seed data added.

`ISASweepGraph` returns an igraph graph object.

`ISASweepGraphPlot` returns `NULL`, invisibly.

### Author(s)

Gabor Csardi csardi.gabor@gmail.com

### References

Bergmann S, Ihmels J, Barkai N: Iterative signature algorithm for the analysis of large-scale gene expression data Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Mar;67(3 Pt 1):031902. Epub 2003 Mar 11.

### Examples

    library(genefilter)
    library(ALL)
    data(ALL)

    varLimit <- 0.5
    kLimit <- 4
    ALimit <- 5
    flist <- filterfun(function(x) var(x)>varLimit, kOverA(kLimit,ALimit))
    ALL.filt <- ALL[genefilter(ALL, flist), ]
    ALL.filt2 <- ALL.filt[, grepl("^B", ALL.filt$BT)]

    # Run ISA
    set.seed(2)
    modules <- ISA(ALL.filt2, flist=NA, thr.gene=seq(2,4,by=0.5), thr.cond=1)

    # Do the sweep
    modules2 <- ISASweep(ALL.filt2, modules)
    modules2

    # Plot it
    ## Not run:
      G <- ISASweepGraph(modules2)
      ISASweepGraphPlot(G)

    ## End(Not run)

[Package eisa version 1.36.0 Index]