Clustering of high-throughput sequencing data by identifying co-expression patterns

Documentation for package ‘clusterSeq’ version 1.17.0

clusterSeq-package	Clustering of high-throughput sequencing data by identifying co-expression patterns
associatePosteriors	Associates posterior likelihood to generate co-expression dissimilarities between genes
cD.ratThymus	Data from female rat thymus tissue taken from the Rat BodyMap project (Yu et al, 2014) and processed by baySeq.
clusterSeq	Clustering of high-throughput sequencing data by identifying co-expression patterns
kCluster	Constructs co-expression dissimilarities from k-means analyses.
makeClusters	Creates clusters from a co-expression minimal linkage data.frame.
makeClustersFF	Creates clusters from a file containing a full dissimilarity matrix.
plotCluster	Plots data from clusterings.
ratThymus	Data from female rat thymus tissue taken from the Rat BodyMap project (Yu et al, 2014).
wallace	Computes Wallace scores comparing two clustering methods.