Similarity-Based Segmentation of Multidimensional Signals

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Documentation for package ‘segmenTier’ version 0.1.2

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Code demos. Use demo() to run them.

Help Pages

segmenTier-package	segmenTier : cluster-based segmentation from a sequential clustering
ash	'asinh' data transformation
backtrace	Back-tracing step of the 'segmenTier' algorithm.
calculateScore	segmenTier's core dynamic programming routine in Rcpp
clusterCor_c	Calculates position-cluster correlations for scoring function "icor".
clusterTimeseries	Cluster a processed time-series with k-means.
colorClusters	Assign colors to clusters.
flowclusterTimeseries	Cluster a processed time-series with 'flowClust' & 'flowMerge'.
logLik.kmeans	Experimental: AIC/BIC for kmeans
log_1	log transformation handling zeros by adding 1
myPearson	Pearson product-moment correlation coefficient
plot.clustering	Plot method for the "clustering" object.
plot.segments	Plot method for the "segments" object.
plot.timeseries	Plot method for the "timeseries" object.
plotdev	Switch between plot devices.
plotSegmentation	Summary plot for the 'segmenTier' pipeline.
print.segments	Print method for segmentation result from 'segmentClusters'.
processTimeseries	Process a time-series for clustering and segmentation.
segmentCluster.batch	Batch wrapper for 'segmentClusters'.
segmentClusters	Run the 'segmenTier' algorithm.
segmenTier	segmenTier : cluster-based segmentation from a sequential clustering
setVarySettings	Parameters for 'segmentCluster.batch'.
sortClusters	Sort clusters by similarity.
tsd	Transcriptome time-series from budding yeast.