NEWS.md

metabolyseR 0.14.10

• Added the method predict() for the RandomForest S4 class to predict model response values.

• Added the method mtry() for the AnalysisData S4 class to return the default mtry random forest parameter for a given response variable.

• Added the method tune() for the AnalysisData S4 class to tune the random forest parameters mtry and ntree for a given response variable.

metabolyseR 0.14.9

• Suppressed name repair console message encountered during random forest permutation testing.

• Added the proximity() method for extracting sample proximities from the RandomForest S4 class.

• Added the mds() method to perform multidimensional scaling on sample proximities from the RandomForest S4 class.

• Added the roc() method to calculate receiver-operator characteristic curves from the RandomForest S4 class.

metabolyseR 0.14.8

• An error is now thrown during random forest classification when less than two classes are specified.

• plotSupervisedRF() now skips plotting if errors are encountered during random forest training.

metabolyseR 0.14.7

• Single replicate classes now automatically removed by plotLDA().

metabolyseR 0.14.6

• plotExplanatoryHeatmap() method for the Analysis class now returns the plot only if the number of plots is equal to 1.

• Removed reference to the nCores parameter from the documentation example of metabolyse().

metabolyseR 0.14.5

• Correlation analysis results now include an absolute correlation coefficient column by which the results are also arranged in descending order.

metabolyseR 0.14.4

• Console output from imputeAll() now suppressed.

metabolyseR 0.14.3

• Temporarily added jasenfinch/missForest as a remote until stekhoven/missForest pull request #25 is resolved.

• The limit of the number of plotted features in plotExplanatoryHeatmap can now be specified using the featureLimit argument.

• plotExplanatoryHeatmap() now returns NULL and returns a message when no explanatory features are found.

• Fixed the alignment of the dendrogram branches with heat map rows in plotExplanatoryHeatmap().

• Fixed ggplot2::guides() warning in plotFeature() and plotTIC().

• Fixed bug in explanatoryFeatures() methods for Analysis class and lists where the threshold was not applied.

• Fixed the error in plotRSD() method for the Analysis class.

• Corrected the text in the modelling vignette concerning the results of using unsupervised random forest for outlier detection.

metabolyseR 0.14.2

• Package version, creation date and verbose argument added to prototype of Analysis class.

• All generics are now defined as standard generics.

• Added metrics method for Analysis class.

• metrics method for lists now ignores list elements that are not of class RandomForest.

metabolyseR 0.14.1

• Changed the RSDthresh argument default to 50% instead of 0.5% in QCrsdFilter generic.

metabolyseR 0.14.0

• Added a NEWS.md file to track changes to the package.

• pkgdown site now available at https://jasenfinch.github.io/metabolyseR/.

• Bug reports and issues URL at https://github.com/jasenfinch/metabolyseR/issues added to package DESCRIPTION.

• Dedicated vignettes now available for a quick start example analysis, data pre-treatment and data modelling.

• Function examples added to all documentation pages.

• Unit test coverage increased to > 95%.

• Parallel processing is now implemented using the future package.

• plan() from the future package is re-exported.

• RandomForest and Univariate classes now inherit from class the AnalysisData class.

• Improvements to plot theme aesthetics.

• type argument added to plotPCA(), plotLDA(), plotUnsupervisedRF() and plotSupervisedRF() methods for the Analysis class.

• "pre-treated" for specifying type argument in Analysis class methods now used over "preTreated"

• Added clsRename() method for renaming class information columns.

• plotMeasures() method renamed to plotMetrics().

• Added plotMDS(), plotImportance() and plotMetrics() methods for lists of RandomForest class objects.

• Added plotExplanatoryHeatmap() method for lists of RandomForest or Univariate class objects.

• Renamed keepVariables() and removeVariables() methods to keepFeatures() and removeFeatures().

• Added the helper functions preTreatmentElements(), preTreatmentMethods() and preTreatParameters() for declaring pre-treatment parameters for the AnalysisParameters class.

• Added the helper functions modellingMethods() and modellingParameters() for declaring modelling parameters for the AnalysisParameters class.

• Added helper function correlationsParameters() for declaring correlations parameters for the AnalysisParameters class.

• Added binaryComparisons() method for retrieving all possible binary class comparisons from an AnalysisData class object.

• changeParameter() now assigns parameter values through direct assignment.

• Added analysisResults() method from extracting analysis elements results from the Analysis class.

• Added exportParameters() method for exporting analysis parameters to YAML file format.

• Added dat() and sinfo() accessor methods for the Analysis class.

• Relative standard deviation (RSD) values are now specified and returned as percentages.