iC10 | R Documentation |
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.
iC10(x, seed=25435)
x |
An object with class |
seed |
seed to initialize random number generator. It is passed to |
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).
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 |
Oscar M. Rueda
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 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)
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