Releases: jasenfinch/metabolyseR
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()
.