ord {made4} | R Documentation

## Ordination

### Description

Run principal component analysis, correspondence analysis or non-symmetric correspondence analysis on gene expression data

### Usage

    ord(dataset, type="coa", classvec=NULL,ord.nf=NULL, trans=FALSE, ...)
    ## S3 method for class 'ord'
    plot(x, axis1=1, axis2=2, arraycol=NULL, genecol="gray25",
     nlab=10, genelabels= NULL, arraylabels=NULL,classvec=NULL, ...)

### Arguments

`dataset` | Training dataset. A `matrix`, `data.frame`, `ExpressionSet` or `marrayRaw-class`. If the input is gene expression data in a `matrix` or `data.frame`. The rows and columns are expected to contain the variables (genes) and cases (array samples) respectively.
`classvec` | A `factor` or `vector` which describes the classes in the training dataset.
`type` | Character, "coa", "pca" or "nsc" indicating which data transformation is required. The default value is type="coa".
`ord.nf` | Numeric. Indicating the number of eigenvector to be saved, by default, if NULL, all eigenvectors will be saved.
`trans` | Logical indicating whether 'dataset' should be transposed before ordination. Used by BGA Default is `FALSE`.
`x` | An object of class `ord`. The output from `ord`. It contains the projection coordinates from `ord`, the \$co or \$li coordinates to be plotted.
`arraycol, genecol` | Character, colour of points on plot. If arraycol is NULL, arraycol will obtain a set of contrasting colours using `getcol`, for each classes of cases (microarray samples) on the array (case) plot. genecol is the colour of the points for each variable (genes) on gene plot.
`nlab` | Numeric. An integer indicating the number of variables (genes) at the end of axes to be labelled, on the gene plot.
`axis1` | Integer, the column number for the x-axis. The default is 1.
`axis2` | Integer, the column number for the y-axis, The default is 2.
`genelabels` | A vector of variables labels, if `genelabels=NULL` the row.names of input matrix `dataset` will be used.
`arraylabels` | A vector of variables labels, if `arraylabels=NULL` the col.names of input matrix `dataset` will be used.
`...` | further arguments passed to or from other methods.

### Details

`ord` calls either `dudi.pca`, `dudi.coa` or `dudi.nsc` on the input dataset. The input format of the dataset is verified using `isDataFrame`.

If the user defines microarray sample groupings, these are colours on plots produced by `plot.ord`.

Plotting and visualising bga results:

2D plots: `plotarrays` to draw an xy plot of cases (\$ls). `plotgenes`, is used to draw an xy plot of the variables (genes).

3D plots: 3D graphs can be generated using `do3D` and `html3D`. `html3D` produces a web page in which a 3D plot can be interactively rotated, zoomed, and in which classes or groups of cases can be easily highlighted.

1D plots, show one axis only: 1D graphs can be plotted using `graph1D`. `graph1D` can be used to plot either cases (microarrays) or variables (genes) and only requires a vector of coordinates (\$li, \$co)

Analysis of the distribution of variance among axes:

The number of axes or principal components from a `ord` will equal `nrow` the number of rows, or the `ncol`, number of columns of the dataset (whichever is less).

The distribution of variance among axes is described in the eigenvalues (\$eig) of the `ord` analysis. These can be visualised using a scree plot, using `scatterutil.eigen` as it done in `plot.ord`. It is also useful to visualise the principal components from a using a `ord` or principal components analysis `dudi.pca`, or correspondence analysis `dudi.coa` using a heatmap. In MADE4 the function `heatplot` will plot a heatmap with nicer default colours.

Extracting list of top variables (genes):

Use `topgenes` to get list of variables or cases at the ends of axes. It will return a list of the top n variables (by default n=5) at the positive, negative or both ends of an axes. `sumstats` can be used to return the angle (slope) and distance from the origin of a list of coordinates.

### Value

A list with a class `ord` containing:

`ord` | Results of initial ordination. A list of class "dudi" (see `dudi`)
`fac` | The input classvec, the `factor` or `vector` which described the classes in the input dataset. Can be NULL.

### Author(s)

Aedin Culhane

### See Also

See Also `dudi.pca`, `dudi.coa` or `dudi.nsc`, `bga`,

### Examples

    data(khan)

    if (require(ade4, quiet = TRUE)) {
      khan.coa<-ord(khan$train, classvec=khan$train.classes, type="coa")
    }

    khan.coa
    plot(khan.coa, genelabels=khan$annotation$Symbol)
    plotarrays(khan.coa)
    # Provide a view of the first 5 principal components (axes) of the correspondence analysis
    heatplot(khan.coa$ord$co[,1:5], dend="none",dualScale=FALSE)

[Package made4 version 1.66.0 Index]