flowclusterTimeseries {segmenTier}

Cluster a processed time-series with flowClust & flowMerge.

Description

A wrapper for flowClust, clustering a time-series object tset provided by processTimeseries, where specifically the DFT of a time-series and requested data transformation were calculated. This is intended to work in the same way as clusterTimeseries but was so far only tested for clustering of the final segment time-series, as previously applied to microarray data from yeast by Machne & Murray (2012) <doi:10.1371/journal.pone.0037906> and from cyanobacteria by Lehmann et al. (2013) <doi:10.1186/1471-2105-14-133>. It could in principle also be used for segmentation, but that has not been extensively tested. flowClust implements a model-based clustering approach and is much slower then kmeans used in clusterTimeseries. Please see option ncpu on how to use parallel mode, which does not work on some installations. However, model-based clustering has the advantage of an intrinsic measure (BIC) to decide on the optimal cluster numbers. Additionally, the clusters can be "merged" to fewer clusters at constant BIC using flowMerge.

Usage

flowclusterTimeseries(tset, ncpu = 1, K = 10, selected,
  merge = FALSE, B = 500, tol = 1e-05, lambda = 1, nu = 4,
  nu.est = 0, trans = 1, ...)

Arguments

tset

processed time-series as provided by processTimeseries

ncpu

number of cores available for parallel mode of flowClust. NOTE: parallel mode of flowClust is often non-functional. Alternatively, you can set options(mc.cores=ncpu) directly.

K

the requested cluster numbers (vector of integers)

selected

a pre-selected cluster number which is then used as a start clustering for flowMerge (if option merge==TRUE)

merge

logical indicating whether cluster merging with flowMerge should be attempted

B

maximal number of EM iterations

tol

tolerance for EM convergence

lambda

initial Box-Cox trafo

nu

degrees of freedom used for the t distribution, Inf for pure Gaussian

nu.est

0: no, 1: non-specific, 2: cluster-specific estimation of nu

trans

0: no, 1: non-specific, 2: cluster-specific estim. of lambda

...

further parameters for flowClust

References

Machne & Murray (2012) <doi:10.1371/journal.pone.0037906>