Changes in version 0.15.4 - Fixed various tidyverse warnings. - Fixed an error when calculating the mds dimensions for multiple class comparisons with differing numbers of observations. - Added the transformPercent() method for the AnalysisData S4 class to scale as a percentage of feature maximum intensity. - Feature intensities are now displayed as relative percent intensities in heat maps generated by plotExplanatoryHeatmap(). - Reduced the gap between the dendrogram and heat map in outputs of plotExplanatoryHeatmap(). Changes in version 0.15.3 - Fixed the margin value displayed in plots from plotSupervisedRF() - The plotExplanatoryHeatmap() method for the Analysis S4 class now returns a warning and skips plotting if an error is encountered whilst trying to plot a heat map. Changes in version 0.15.2 - Added the argument refactor to the method transformTICnorm() to enable the feature intensities of total ion count (TIC) normalised data to be refactored back to a range consistent with the original data by multiplying the normalised values by the median TIC. - Removed the permutation cap when the perm argument of randomForest() is less than the total number of permutations possible. Changes in version 0.15.1 - The class occupancy methods now throw a helpful error message if no features are available on which to compute class occupancy. - Fixed a bug where it was not possible to customize the order of class labels in the legend of plotLDA(). Changes in version 0.15.0 - It is now possible to specify multiple cls arguments to the aggregation methods. - Correlation thresholds are now available for both coefficient and total number using the minCoef and maxCor arguments in the correlations() method. - Added the predictions() accessor method for the RandomForest S4 class to enable the retrieval of the out of bag model response predictions. - The occupancy filtering methods now error if the value supplied to argument occupancy is non-numeric. - Memory usage and performance improvements for the randomForest() method. - Added type() and response() methods for the Univariate S4 class. - plotLDA() now returns a warning and skips plotting if an error is encountered during PC-LDA. - The value pre-treated is now the default for argument type in the Analysis S4 class accessor methods. - Added the value argument to the explanatoryFeatures() method to allow the specification of on which importance value to apply the specified threshold. - The specified cls argument is now correctly displayed on the x-axis title of the resulting plots from the plotFeature() method. Changes in version 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. Changes in version 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. Changes in version 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. Changes in version 0.14.7 - Single replicate classes now automatically removed by plotLDA(). Changes in version 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(). Changes in version 0.14.5 - Correlation analysis results now include an absolute correlation coefficient column by which the results are also arranged in descending order. Changes in version 0.14.4 - Console output from imputeAll() now suppressed. Changes in version 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. Changes in version 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. Changes in version 0.14.1 - Changed the RSDthresh argument default to 50% instead of 0.5% in QCrsdFilter generic. Changes in version 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.