Package: clusterSeq 1.36.0

Samuel Granjeaud

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

Identification of clusters of co-expressed genes based on their expression across multiple (replicated) biological samples.

Authors:Thomas J. Hardcastle [aut], Irene Papatheodorou [aut], Samuel Granjeaud [cre]

# Install 'clusterSeq' in R:

install.packages('clusterSeq', repos = c('https://bioc-release.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

cD.ratThymus - Data from female rat thymus tissue taken from the Rat BodyMap project (Yu et al, 2014) and processed by baySeq.
ratThymus - Data from female rat thymus tissue taken from the Rat BodyMap project (Yu et al, 2014).

On BioConductor:clusterSeq-1.37.0(bioc 3.24)clusterSeq-1.36.0(bioc 3.23)

Last updated from:e53b3fc46a (on RELEASE_3_23). Checks:1 WARNING, 9 OK. Indexed: no.

Target	Result	Time
bioc-checks	WARNING	140
linux-devel-x86_64	OK	404
source / vignettes	OK	232
linux-release-x86_64	OK	330
macos-release-arm64	OK	271
macos-oldrel-arm64	OK	327
windows-devel	OK	422
windows-release	OK	377
windows-oldrel	OK	434
wasm-release	OK	123

Last update: 2018-08-30
Started: 2016-12-12

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