plot.iC10: Plot results of the iC10 classifier
In iC10: A Copy Number and Expression-Based Classifier for Breast Tumours

Description Usage Arguments Details Value Author(s) References See Also Examples

Plot results of the iC10 classifier, in two different formats: either the signatures of the training set or the signatures of the new data classified.

1 2	## S3 method for class 'iC10' plot(x, sample.name=1, newdata = NULL,...)

`x`	An object of `iC10` class:
`sample.name`	Number of sample to plot (if `newdata` is NULL). It can be either a number or a character with the sample name.
`newdata`	An object result to call to `matchFeatures` or `normalizeFeatures` containing the features of the samples to plot.
`...`	Additional arguments passed to `plot`.

Two types of plots can be produced. If newdata is NULL, a panel 6x2 is drawn with the 10 profiles of the signatures of the training set and the profile of the features of sample.name and the distribution of the probabilities of classification to each iC10 for that sample. If newdata is not nutll, a panel 6x2 (with the 11th panel empty) is drawn with the 10 profiles of newdata samples and their distribution into the clusters. The features are sorted by type: copy number (if available) are drawn in grey, and then expression, each of them are sorted by genomic position.

A 6x2 plot is produced.

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.

iC10

require(iC10TrainingData)
data(train.CN)
data(train.Exp)
features <- matchFeatures(Exp=train.Exp, Exp.by.feat="probe")
features <- normalizeFeatures(features, "scale")
res <- iC10(features)
plot(res, sample.name=10)
plot(res, newdata=features)