orderFeatures {hddplot} | R Documentation

## Order features, based on their ability to discriminate

### Description

For each row of `data`, an F or (potentially) other statistic is calculated, using the function `FUN`, that measures the extent to which this variable separates the data into groups. This statistic is then used to order the rows.

### Usage

     orderFeatures(x, cl, subset = NULL, FUN = aovFbyrow, values =
    FALSE)

### Arguments

`x` | Matrix; rows are features, and columns are observations ('samples')
`cl` | Factor that classifies columns into groups
`subset` | allows specification of a subset of the columns of `data`
`FUN` | specifies the function used to measure separation between groups
`values` | if `TRUE`, F-values as well as the ordering are returned

### Details

### Value

Either (`values=FALSE`) a vector that orders the rows, or (`values=TRUE`)

`ord` | a vector that orders the rows
`stat` | ordered values of the statistic

### Note

### Author(s)

John Maindonald

### References

### See Also

~~objects to See Also as `help`, ~~~

### Examples

    mat <- matrix(rnorm(1000), ncol=20)
    cl <- factor(rep(1:3, c(7,9,4)))
    ord <- orderFeatures(mat, cl)

    ## The function is currently defined as
    function(x, cl, subset=NULL, FUN=aovFbyrow, values=FALSE){
        if(dim(x)[2]!=length(cl))stop(paste("Dimension 2 of x is",
                      dim(x)[2], "differs from the length of cl (=",
                      length(cl)))
        ## Ensure that cl is a factor & has no redundant levels
        if(is.null(subset))
          cl <- factor(cl)
        else
          cl <- factor(cl[subset])
        if(is.null(subset))
          stat <- FUN(x, cl)
        else
          stat <- FUN(x[, subset], cl)
        ord <- order(-abs(stat))
        if(!values)ord else(list(ord=ord, stat=stat[ord]))
      }

[Package hddplot version 0.51 Index]