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NEWS.md

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metabolyseR 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().

metabolyseR 0.15.3

metabolyseR 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.

metabolyseR 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().

metabolyseR 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.

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

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

metabolyseR 0.14.3

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.