summary.coseq: Summarize results from clustering using a Poisson or Gaussian...

In coseq: Co-Expression Analysis of Sequencing Data

Description

A function to summarize the clustering results obtained from a Poisson or Gaussian mixture model estimated using coseq.

Usage

## S3 method for class 'coseq'
summary(object, ...)

Arguments

object	An object of class "coseq"
...	Additional arguments

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

coseq

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

## Run the Normal mixture model for K = 2,3,4
run_arcsin <- coseq(y=countmat, K=2:4, iter=5, transformation="arcsin")

## Plot and summarize results
plot(run_arcsin)
summary(run_arcsin)

## Compare ARI values for all models (no plot generated here)
ARI <- compareARI(run_arcsin, plot=FALSE)

## Compare ICL values for models with arcsin and logit transformations
run_logit <- coseq(y=countmat, K=2:4, iter=5, transformation="logit")
compareICL(list(run_arcsin, run_logit))

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