# Similarity-Based Segmentation of Multidimensional Signals

## 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.