discretize.tscores {macat} | R Documentation

## Discretize regularized t-scores

### Description

discretize.tscores returns a discretized version of the scores in the MACATevalScoring object. Discretization is performed by comparing the value gene-wise (location-wise) with the symmetric upper and lower quantile given by margin (in percent margin/2 lower and upper quantile). discretizeAllClasses produces a flatfile readable by PYTHON.

### Usage

    discretize.tscores(scores)
    discretizeAllClasses.tscores(data, chrom, nperms=10, kernel=rbf, kernelparams=NULL, step.width=100000)

### Arguments

`scores` | a MACATevalScoring object obtained from evalScoring
`data` | a MACATData Object containing all expression values, geneLocations and labels (obtained from preprocessedLoader)
`chrom` | chromosome that is discretized
`nperms` | number of permutations for the computation of empirical p values (evalScoring)
`kernel` | kernel function used for smoothing one of rbf, kNN, basePairDistance or your own
`kernelparams` | list of parameters for the kernels
`step.width` | size of a interpolation step in basepairs

### Details

The filename for the python flat files are `discrete_chrom_<chrom>_class_<label>.py` where <chrom> and <label> are the names of the chromosome and class label.

### Value

`discretize.tscores` | a vector of discretized tscores
`discretizeAllClasses.tscores` | creates python flatfiles (see details)

### Author(s)

The MACAT development team

### See Also

`evalScoring`, `kernels`, `pythondata`

### Examples

      #loaddatapkg("stjudem")
      data(stjd)
      # simple scoring with short running time
      scores = evalScoring(stjd, "T", 1, nperms=100, cross.validate=FALSE)
      discrete = discretize.tscores(scores)

[Package macat version 1.18.0 Index]