iC10: A copy number and expression-based classfier for breast...

In iC10: A Copy Number and Expression-Based Classifier for Breast Tumours

A copy number and expression-based classfier for breast cancers

Description

iC10 implements the classifier described in the paper 'Genome-driven integrated classification of breast cancer validated in over 7,500 samples' (Ali HR et al., Genome Biology 2014). It uses copy number and/or expression form breast cancer data, trains a pamr classifier (Tibshirani et al.) with the features available and predicts the iC10 group.

Usage

iC10(x, seed=25435)

Arguments

x	An object with class iC10features: A list with elements 'train.CN', 'train.Exp', 'train.iC10', 'CN', 'Exp', 'map.cn', 'map.exp'
seed	seed to initialize random number generator. It is passed to set.seed(). See details.

Details

This function trains a pamr classifier and predicts the set of samples. The shrinkage parameter is obtained with crossvalidation, therefore different runs can give different results (unless a seed is specified).

Value

An object of class iC10. A list with the following elements:

class	Prediction classes for the samples
posterior	Probablitites for each sample to belong to each of the 10 groups
centroids	Shrunken Centroids for each of the 10 groups.
fitted	Normalized features for the samples classified.
map.cn	Annotation data for the copy number features
map.exp	Annotation data for the expression features

Author(s)

Oscar M. Rueda

References

Ali HR et al. Genome-driven integrated classification of breast cancer validated in over 7,500 samples. Genome Biology 2014; 15:431. Curtis et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 2012; 486:346-352. Tibshirani et al. Diagnosis of multiple cancer types by shrunken centroids of gene expression. PNAS 2002; 99(10):6567-6572.

See Also

See pamr.train, pamr.cv and pamr.predict in package pamr.

Examples

require(iC10TrainingData)
data(train.CN)
data(train.Exp)
features <- matchFeatures(Exp=train.Exp, Exp.by.feat="probe")
features <- normalizeFeatures(features, "scale")
res <- iC10(features)

iC10 documentation built on Sept. 11, 2024, 6:22 p.m.