claudinLow {genefu} | R Documentation

## Claudin-low classification for Breast Cancer Data

### Description

Subtyping method for identifying Claudin-Low Breast Cancer Samples. Code generously provided by Aleix Prat.

### Usage

    claudinLow(x, classes="", y, nGenes="", priors="equal",
      std=FALSE, distm="euclidean", centroids=FALSE)

### Arguments

`x` | the data matrix of training samples, or pre-calculated centroids.
`classes` | a list labels for use in coloring the points.
`y` | the data matrix of test samples.
`nGenes` | the number of genes selected when training the model.
`priors` | 'equal' assumes equal class priors, 'class' calculates them based on proportion in the data.
`std` | when true, the training and testing samples are standardized to mean=0 and var=1.
`distm` | the distance metric for determining the nearest centroid, can be one of euclidean, pearson, or spearman.
`centroids` | when true, it is assumed that x consists of pre-calculated centroids.

### Value

A list with items:

- predictions

- testData

- distances

- centroids

### References

Aleix Prat, Joel S Parker, Olga Karginova, Cheng Fan, Chad Livasy, Jason I Herschkowitz, Xiaping He, and Charles M. Perou (2010) "Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer", Breast Cancer Research, 12(5):R68

### See Also

`medianCtr()`, q

### Examples

    data(claudinLowData)

    #Training Set
    train <- claudinLowData
    train$xd <-  medianCtr(train$xd)
    # Testing Set
    test <- claudinLowData
    test$xd <-  medianCtr(test$xd)

    # Generate Predictions
    predout <- claudinLow(x=train$xd, classes=as.matrix(train$classes$Group,ncol=1), y=test$xd)

    # Obtain results
    results <- cbind(predout$predictions, predout$distances)
    #write.table(results,"T.E.9CELL.LINE_results.txt",sep="\t",col=T, row=FALSE)

[Package genefu version 2.26.0 Index]