MolecularPermutationClassifier-class {pbcmc} | R Documentation

## Class `MolecularPermutationClassifier` S4 implementation in R

### Description

Virtual class to represent gene-based molecular signature classification by means of permutation test.

### Slots

`parameters`

  named list with at least the following fields:

  $nPerm

    integer with number of permutations. Default: 1e4L

  $where

    character with significant value used. Default value is "fdr".

  $pCutoff

    numeric with p-value or fdr cutoff used, i.e., variable<pCutoff. Default: 0.01

  $keep

    should null distribution simulation values be kept?. Default: FALSE

`exprs`

  matrix with gene exprs profile, where genes are in rows and subjects as columns, a.k.a., M matrix.

`annotation`

  data.frame with individual annotations (genes, etc). Minimal compulsory fields are:

  $probe

    same characters as in row.names(M).

  $EntrezGene.ID

    integer with NCBI Entrez Data Base.

  $NCBI.gene.symbol

    character with gene mnemonic, a.k.a. gene symbol.

`targets`

  data.frame with additional subject data (optional).

`classification`

  named list with at least the following fields:

  $class

    factor with all possible class levels.

`permutation`

  named list with at least the following fields:

  $pvalues

    numeric matrix with subjects in row and classes in columns.

  $fdr

    numeric matrix with False Discovery Rate correction of p-values by row.

### Superclasses

None declared.

### Subclasses

PAM50

  Peruo et al. (2000 and 2010) breast cancer subtypes, i. e., Luminal A, Luminal B, Basal, Her2 or Normal-like subtypes as implemented in genefu library (Haibe-Kains et al. 2014).

### Functions

MolecularPermutationClassifier S4 class includes the following functions:

- Integrity check:

  validity

    will check appropriate annotation data.frame minimal required columns, all named parameters and if exprs and annotation dimension matches.

  prototype

    just for an empty class with default values: nPerm=1e4L, where="fdr", pCutoff=0.01, corCutoff=0.1 and keep=FALSE

  .

- Generics:

  `show`,`print`

    basic class display wrappers.

  `summary`

    classifier statistics.

- Constructors (as this class is virtual see subclass' 'documentation).

  `setAs`

    MAList to `PAM50`

  `as.PAM50`

    wrapper for `PAM50` setAs from MAList.

  `loadBCDataset`

    wrapper to load BreastCancerXX data (Class, exprs, annotation, clinical data).

- Getters for the corresponding slots (`parameters`, `exprs`, `annotation`, `targets`, `classification` and `permutation`).

- Setters for the corresponding slots (`parameters<-`, `annotation<-` and `targets<-`).

- Particular (virtual) functions:

  `filtrate`

    remove from the `exprs` matrix subjects not required by the classification algorithm.

  `classify`

    generate subject classification according to subclasses implementation (PAM50, etc.).

  `permutate`

    obtain subject classification based on the null correlation distribution by means permutation simulation.

  `subtypes`

    obtain the new classification using permutation results.

  `subjectReport`

    a friendly report for Physician treatment decision support.

  `databaseReport`

    a pdf with all subjectReports, if a database is available.

### Author(s)

Cristobal Fresno cfresno@bdmg.com.ar, German A. Gonzalez ggonzalez@bdmg.com.ar, Andrea S. Llera allera@leloir.org.ar and Elmer Andres Fernandez efernandez@bdmg.com.ar

### References

1. Haibe-Kains B, Schroeder M, Bontempi G, Sotiriou C and Quackenbush J, 2014, genefu: Relevant Functions for Gene Expression Analysis, Especially in Breast Cancer. R package version 1.16.0, www.pmgenomics.ca/bhklab/

2. Perou CM, Sorlie T, Eisen MB, et al., 2000, Molecular portraits of human breast tumors. Nature 406:747-752

3. Perou CM, Parker JS, Prat A, Ellis MJ, Bernard PB., 2010, Clinical implementation of the intrinsic subtypes of breast cancer, The Lancet Oncology 11(8):718-719

### See Also

`PAM50` for a complete example, `loadBCDataset` to load BreastCancerXX dataset, `filtrate`, `classify` and `permutate` to get corresponding Breast Cancer subtype. Getters/Setters for this class are `parameters`, `exprs`, `annotation`, `targets`, `classification` and `permutation`.

Other MolecularPermutationClassifier: `parameters`, `show`

[Package pbcmc version 1.8.0 Index]