pbcmc (version 1.0.0)

parameters: Accessors for MolecularPermutationClassifier child class slots

Description

Slot setters/getters for MolecularPermutationClassifier hierarchy classes

Usage

parameters(object)
"parameters"(object)
parameters(object) <- value  
"parameters"(object) <- value  
"exprs"(object)
"exprs"(object) <- value  
"annotation"(object, ...)   
"annotation"(object) <- value  
targets(object)
"targets"(object)
targets(object) <- value  
"targets"(object) <- value  
classification(object)
"classification"(object)
permutation(object)
"permutation"(object)

Arguments

object

MolecularPermutationClassifier subclass object

value

according to the function call:

• 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

  $corCutoff

  numeric with correlation difference between classes cutoff used, i.e., $|\rho(profile,class_A)-\rho(profile,class_B)|>corCutoff$

  $keep

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

• 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.

• exprs: matrix with gene exprs profile, where genes are in rows and subjects as columns, a.k.a., M matrix.
• targets: data.frame with additional subject data.

...

additional parameters according to function call.

Value

according to function call one of the following objects:

parameters

named list see value parameter

exprs

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

annotation

data.frame see value parameter

classification

named list with at least the following fields:

$class

factor with 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 pvalues by row.

parameters<-

MolecularPermutationClassifier object with parameters updated slot.

exprs<-

MolecularPermutationClassifier object with exprs updated slot.

annotation<-

MolecularPermutationClassifier object with annotation updated slot.

targets<-

MolecularPermutationClassifier object with targets updated slot.

See Also

PAM50 for a complete example.

Other MolecularPermutationClassifier: MolecularPermutationClassifier-class, show

Examples

##Using pam50centroids package example data
data(pam50centroids)

##Now we can inspect pam50centroids object   
head(exprs(pam50centroids))      ##The gene expression
head(annotation(pam50centroids)) ##The available annotation 
head(targets(pam50centroids))    ##The clinical data present in the package  

##Work with the parameters 
parameters(pam50centroids)       ##Display them
aux<-parameters(pam50centroids)    
aux$keep<-TRUE                   ##Set keep to FALSE  
parameters(pam50centroids)<-aux
parameters(pam50centroids)        

##Also exprs<-, annotation<- and targets<- available functions to update    
##the respective slots