Man pages for computational-metabolomics/structtoolbox
Some tools bult using the struct package

ANOVA-classANOVA
autoscale-classAutoscale
balanced_accuracy-classBalanced Accuracy
blank_filter-classBlank filter
blank_filter.hist-classplot for blank filter
calculateCalculate metric
chart.plotchart.plot
classical_lsq-classClassical Least Squares regression
compare_dist-classCompare distributions
confounders_clsq-classCheck for confounding factors in ttest
confounders_lsq.barchart-classbarchart of percent change
confounders_lsq.boxplot-classboxplot of percent change
corr_coef-classcorrelation model class
dataset.boxplot-classDataset boxplot
dataset.dist-classDistribution plot
dataset.factor_barchart-classdataset.factor_barchart class
dataset.heatmap-classdataset.heatmap class
dratio_filter-classD ratio filter
feature_boxplot-classfeature_boxplot class
feature_profile-classfeature_profile class
filter_by_name-classfilter by name
filter_na_count-classfilter_na_count class
filter_smeta-classfilter_smeta class
fisher_exact-classfisher_exact class
fold_change-classfold change class
fold_change_int-classfold change for interactions class
fold_change_plot-classfold_change plot
forward_selection_byrank-classforward selection by rank
fs_line-classforward_selection_plot
glog_transform-classglog transform
grid_search_1d-classgrid_search_1d class
gs_line-classgrid_search_plot
HCA-classHCA method class
hca_dendrogram-classhca_dendrogram class
HSD-classHSD model class
HSDEM-classHSD model class using estimated marginal means
kfoldxcv_grid-classkfoldxcv_grid class
kfoldxcv_metric-classkfoldxcv_metric class
kfold_xval-classkfold_xval model class
knn_impute-classknn missing value imputation
kw_p_hist-classplot histogram of p values
kw_rank_sum-classkruskal-wallis model class
linear_model-classlinear model class
log_transform-classlog transform
mean_centre-classmean_centre model class
method.applyApply method
mixed_effect-classMixed Effects model class
model.predictModel prediction
model.reverseReverse preprocessing
model.trainTrain a model
mv_boxplot-classmv_boxplot class
mv_feature_filter-classfilter features by fraction missing values
mv_feature_filter.hist-classplot for missing value sample filter
mv_histogram-classmv_histogram class
mv_sample_filter-classmissing value filter (samples)
mv_sample_filter.hist-classplot for missing value sample filter
pairs_filter-classPairs filter
pca_biplot_plot-classpca_biplot_plot class
PCA-classPCA model class
pca_correlation_plot-classpca_correlation_plot class
PCA.dstat-classpca_dstat_plot class
pca_loadings_plot-classpca_loadings_plot class
pca_scores_plot-classpca_scores_plot class
PCA.scree-classpca_scree_plot class
permutation_test.boxplot-classpermutation_test.boxplot class
permutation_test-classpermutation test class
permutation_test.hist-classpermutation_test.hist class
permutation_test.scatter-classpermutation_test.scatter class
permutation_test.violin-classpermutation_test.violin class
permute_sample_order-classpermute_sample_order class
PLSDA-classPLSDA model class
plsda_scores_plot-classplsda_scores_plot class
PLSFC-classPLS fold change
PLSR-classPLSR model class
plsr_cook_dist-classplsr_residual_plot class
plsr_prediction_plot-classplsr_prediction_plot class
plsr_qq_plot-classplsr_qq_plot class
plsr_residual_hist-classplsr_residual_hist class
pqn_norm-classPQN nromalisation
pqn_norm.hist-classplot for PQN normalisation
prop_na-classprop_na model class
rsd_filter-classrsd filter
rsd_filter.hist-classplot for rsd filter
r_squared-classCoefficient of determination class
runRuns an iterator, applying the chosen model multiple times.
sbcms_datasetData from sbcms
sb_corr-classsbcms
split_data-classsplit data into sets
structToolboxstructToolbox: Examples of tools built using the Statistics...
tSNE-classtSNE method class
tSNE_scatter-classtSNE_scatter class
ttest-classt-test model class
vec_norm-classvector nromalisation
wilcox_p_hist-classplot histogram of p values
wilcox_test-classwilcoxon signed rank test method class
computational-metabolomics/structtoolbox documentation built on Oct. 10, 2019, 7:11 p.m.