Changelog
Source:NEWS.md
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 theAnalysisData
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
Fixed the margin value displayed in plots from
plotSupervisedRF()
The
plotExplanatoryHeatmap()
method for theAnalysis
S4 class now returns a warning and skips plotting if an error is encountered whilst trying to plot a heat map.
metabolyseR 0.15.2
Added the argument
refactor
to the methodtransformTICnorm()
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 ofrandomForest()
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
andmaxCor
arguments in thecorrelations()
method.Added the
predictions()
accessor method for theRandomForest
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()
andresponse()
methods for theUnivariate
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 argumenttype
in theAnalysis
S4 class accessor methods.Added the
value
argument to theexplanatoryFeatures()
method to allow the specification of on which importance value to apply the specifiedthreshold
.The specified
cls
argument is now correctly displayed on the x-axis title of the resulting plots from theplotFeature()
method.
metabolyseR 0.14.10
Added the method
predict()
for theRandomForest
S4 class to predict model response values.Added the method
mtry()
for theAnalysisData
S4 class to return the defaultmtry
random forest parameter for a given response variable.Added the method
tune()
for theAnalysisData
S4 class to tune the random forest parametersmtry
andntree
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 theRandomForest
S4 class.Added the
mds()
method to perform multidimensional scaling on sample proximities from theRandomForest
S4 class.Added the
roc()
method to calculate receiver-operator characteristic curves from theRandomForest
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 theAnalysis
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 ofmetabolyse()
.
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 thefeatureLimit
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 inplotFeature()
andplotTIC()
.Fixed bug in
explanatoryFeatures()
methods forAnalysis
class and lists where the threshold was not applied.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 forAnalysis
class.metrics
method for lists now ignores list elements that are not of classRandomForest
.
metabolyseR 0.14.1
- Changed the
RSDthresh
argument default to 50% instead of 0.5% inQCrsdFilter
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.RandomForest
andUnivariate
classes now inherit from class theAnalysisData
class.Improvements to plot theme aesthetics.
type
argument added toplotPCA()
,plotLDA()
,plotUnsupervisedRF()
andplotSupervisedRF()
methods for theAnalysis
class."pre-treated"
for specifying type argument inAnalysis
class methods now used over"preTreated"
Added
clsRename()
method for renaming class information columns.plotMeasures()
method renamed toplotMetrics()
.Added
plotMDS()
,plotImportance()
andplotMetrics()
methods for lists ofRandomForest
class objects.Added
plotExplanatoryHeatmap()
method for lists ofRandomForest
orUnivariate
class objects.Renamed
keepVariables()
andremoveVariables()
methods tokeepFeatures()
andremoveFeatures()
.Added the helper functions
preTreatmentElements()
,preTreatmentMethods()
andpreTreatParameters()
for declaring pre-treatment parameters for theAnalysisParameters
class.Added the helper functions
modellingMethods()
andmodellingParameters()
for declaring modelling parameters for theAnalysisParameters
class.Added helper function
correlationsParameters()
for declaring correlations parameters for theAnalysisParameters
class.Added
binaryComparisons()
method for retrieving all possible binary class comparisons from anAnalysisData
class object.changeParameter()
now assigns parameter values through direct assignment.Added
analysisResults()
method from extracting analysis elements results from theAnalysis
class.Added
exportParameters()
method for exporting analysis parameters to YAML file format.Added
dat()
andsinfo()
accessor methods for theAnalysis
class.Relative standard deviation (RSD) values are now specified and returned as percentages.