MAIT_identify_metabolites
MAIT metabolite identification
Apply function to samples
convert_keggpathway_2_reactiongraph
Convert KEGGPathway object to graph object.
Analysis of variance
Convert metadata to factor
Background correction
Baseline correction
Apply by group
Boxplot of variables
detect_nmr_peaks_from_dataset
Detection of the peaks in an NMR spectra dataset.
Boxplot of variables with metadata's variable factors
Perform cluster analysis
Apply function to variables
Apply by groups
Perform feature selection
Get all organisms in KEGG.
Human Cachexia data
compare_regions_by_sample
Compare regions by sample
Get the names of the compounds that correspond to the kegg codes given.
Get metadata
Cassava Postharvest Physiological Deterioration
Count missing values
create_pathway_with_reactions
Creates the pathway, with reactions included in the nodes.
count_missing_values_per_sample
Count missing values per sample
Find the best correlation value for the clustering of peaks
Check dataset
Cubic root transformation
Choose the metabolites' spectra to be the reference.
Perform selection by filter
Get type of data
Get metadata value
Create dataset
Dataset correlations
Correlations test
Correlation test of two variables or samples
get_metabolights_study_list
List of metabolights studies available to download.
Convert to hyperspec
count_missing_values_per_variable
Count missing values per variable
Download Metabolights study files.
Find equal samples
Convert from hyperspec
Get value label
Plot dendrogram
Get x-axis label
Get x-axis values as numbers
Convert HMDB codes to KEGG codes.
Impute missing values with KNN
Plot dendrogram
Get x-axis values as text
Impute missing values with linear approximation
Flat pattern filter
Linear regression coefficient table
Group peaks
Check type of data
First derivative
Data correction
Jaccard Index
Linear regression p-values table
Logarithmic transformation.
Dataset from peaks
Data frame with the connections between the metabolic pathways.
Cluster of variables (peaks) in a NMR peaks dataset for metabolite identification.
Low level fusion
Fold change analysis
Get data
Fold change applied on two variables
Get data value
Get the metabolic pathways present in given organism.
Returns an object of KEGGPathway of the pathway especified in pathcode.
HMDB code and name of HMDB 1d-NMR spectra.
Get data as data frame
Get sample's names from DX files
Mean centering
Get sample's names from SPC files
Impute missing values with value replacement
indexes_to_xvalue_interval
Get the x-values of a vector of indexes
Multifactor ANOVA
multifactor_aov_pvalues_table
Multifactor ANOVA p-values table
Get data values
Get peak values
3D PCA biplot (interactive)
Get sample names
Impute missing values with median
Impute missing values with mean
Kolmogorov-Smirnov tests on dataset
Get metadata variable
Function to do NMR metabolite identification
PCA importance
Linear regression r-squared
2D PCA scores plot
Linear Regression
Get only the paths of the organism that contain one or more of the given compounds.
Correlations heatmap
Linear regression on one variable
3D PCA scores plot
Perform hierarchical clustering analysis
PCA analysis (classical)
List of reference 1D-NMR peak lists.
Conditions of acquirement of the different refernece peak lists.
Plot the peaks of a MS or NMR dataset.
plot_regression_coefs_pvalues
Plot regression coefficient and p-values
Show cluster's members
Perform k-means clustering analysis
Normalize data
Predict samples
PCA biplot
Kruskal-Wallis tests on dataset
Normalize samples
Metadata as variables
3D pca plot
Missing values imputation
PCA analysis (robust)
Plot Kruskal-Wallis tests results
Brazilian Propolis from different Harvest Seasons and different Agroecological Regions (dataset)
3D PCA scores plot (interactive)
multifactor_aov_varexp_table
Multifactor ANOVA variability explained table
recursive_feature_elimination
Perform recursive feature elimination
Merge data and metadata
Plot kmeans clusters
PCA scree plot
Read CSV data
Multiplot
Plot Kolmogorov-Smirnov tests results
Get number of samples
Read data from (J)DX files
Remove data
Merge two datasets
Get number of x values
Multiplicative scatter correction
Read metadata
Read MS spectra
Remove samples
2D PCA k-means plot
Plot ANOVA results
Plot spectra
Multi Class Summary
3D PCA k-means plot (interactive)
Plot fold change results
Offset correction
Remove samples by NAs
Replace metadata's value
Remove variables by NAs
Plot t-tests results
Creates the metabolic pathway wanted. If any of the given compounds is present in the pathway, it is coloured differently.
remove_samples_by_na_metadata
Remove samples by NA on metadata
Set new x-values
Plot variable distribution on two factors
PCA k-means pairs plot
Shift correction
Peaks per sample
PCA pairs plot
Read dataset from (J)DX files
Savitzky-golay transformation
Read dataset from SPC files
Peaks per samples
Read Bruker processed spectra.
Plot spectra (simple)
Subset samples
Read CSVs from folder
Smoothing interpolation
Standard Normal Variate
remove_x_values_by_interval
Remove x-values by interval
Replace data value
subset_samples_by_metadata_values
Subset samples by metadata values
Dataset summary
Subset x-values
subset_x_values_by_interval
Subset x-values by interval
Scale dataset
Brazilian Propolis from different Harvest Seasons and different Agroecological Regions (sample list)
Import for Thermo Galactic's spc file format
These functions allow to import .spc files.
Summary of variables importance
Scale data matrix
Get x-values indexes
Statistics of variables
Read data from SPC files
Function that reads raw spectra (intensity over time spectra) from the varian format and processes them to ppm spectra.
xvalue_interval_to_indexes
Get indexes of an interval of x-values
Read multiple CSVs
t-Tests on dataset
subset_by_samples_and_xvalues
Subset by samples and x-values
Train and predict
Read dataset from CSV
Variables as metadata
Remove interval of peaks
Set value label
remove_peaks_interval_sample_list
Remove interval of peaks (sample list)
Set x-label
Remove data variables
Volcano plot
Brazilian Propolis from different Harvest Seasons and different Agroecological Regions
remove_metadata_variables
Remove metadata's variables
Set new metadata
Train classifier
Statistics of samples
Set samples names
Train models
Subset metadata
Subset random samples
Transform data
transmittance_to_absorbance
Convert transmittance to absorbance
Values per peak
Values per peak
absorbance_to_transmittance
Convert absorbance to transmittance
Aggregate samples
Conversion table.
Convert from ChemoSpec