summary.NormMixClus: Summarize results from clustering using a Normal mixture...

In coseq: Co-Expression Analysis of Sequencing Data

Description

A function to summarize the clustering results obtained from a Normal mixture model estimated using NormMixClus.

Usage

## S3 method for class 'NormMixClus'
summary(object, y_profiles, digits = 3, ...)

Arguments

object	An object of class "NormMixClus"
y_profiles	y (n x q) matrix of observed profiles for n observations and q variables
digits	Integer indicating the number of decimal places to be used for mixture model parameters
...	Additional arguments

Details

The summary function for an object of class "NormMixClus" provides the number of clusters selected for the ICL model selection approach.

Author(s)

Andrea Rau

References

Rau, A. and Maugis-Rabusseau, C. (2016) Transformation and model choice for co-expression analayis of RNA-seq data. bioRxiv, doi: http://dx.doi.org/10.1101/065607.

See Also

NormMixClus, NormMixClus_K

Examples

## Simulate toy data, n = 300 observations
set.seed(12345)
countmat <- matrix(runif(300*4, min=0, max=500), nrow=300, ncol=4)
countmat <- countmat[which(rowSums(countmat) > 0),]
profiles <- transform_RNAseq(countmat, norm="none", 
                             transformation="arcsin")$tcounts

conds <- rep(c("A","B","C","D"), each=2)

## Run the Normal mixture model for K = 2,3
run <- NormMixClus(y=profiles, K=2:3, iter=5)

## Run the Normal mixture model for K=2
run2 <- NormMixClus_K(y=profiles, K=2, iter=5)

## Re-estimate mixture parameters for the model with K=2 clusters
param <- NormMixParam(run2, y_profiles=profiles)

## Summary of results
summary(run, y_profiles=profiles)

coseq documentation built on May 2, 2019, 4:55 p.m.