ts2MRexperiment: With a list of fitTimeSeries results, generate an...

In metagenomeSeq: Statistical analysis for sparse high-throughput sequencing

Description

With a list of fitTimeSeries results, generate an MRexperiment that can be plotted with metavizr

Usage

ts2MRexperiment(
  obj,
  sampleNames = NULL,
  sampleDescription = "timepoints",
  taxonomyLevels = NULL,
  taxonomyHierarchyRoot = "bacteria",
  taxonomyDescription = "taxonomy",
  featuresOfInterest = NULL,
  featureDataOfInterest = NULL
)

Arguments

obj	Output of fitMultipleTimeSeries
sampleNames	Sample names for plot
sampleDescription	Description of samples for plot axis label
taxonomyLevels	Feature names for plot
taxonomyHierarchyRoot	Root of feature hierarchy for MRexperiment
taxonomyDescription	Description of features for plot axis label
featuresOfInterest	The features to select from the fitMultipleTimeSeries output
featureDataOfInterest	featureData for the resulting MRexperiment

Value

MRexperiment that contains fitTimeSeries data, featureData, and phenoData

See Also

fitTimeSeries fitMultipleTimeSeries

Examples

data(mouseData)
res = fitMultipleTimeSeries(obj=mouseData,lvl='phylum',class="status",
          id="mouseID",time="relativeTime",B=1)
obj = ts2MRexperiment(res)
obj

metagenomeSeq documentation built on Nov. 8, 2020, 5:34 p.m.