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