# A High-Performance R Package for Metabolomics Modeling and Analysis

## Documentation for package ‘metabom8’ version 1.0.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

metabom8-package | metabom8: A High-Performance R Package for Metabolomics Modeling and Analysis
.perm_test_from_table | Permutation-test summary from an opls_perm out_df table
add_note | Add user note to metabom8 provenance Appends a user annotation to the '"m8_prep"' attribute. The step title is formatted as '"note {username}"'. The timestamp is stored in 'params', and the user message is stored in 'notes'.
align_segment | Align NMR Spectra in a Selected Shift Region
align_spectra | Cohort-Guided Interval Alignment for 1D NMR Spectra
balanced_boot | Balanced bootstrap resampling strategy
balanced_mc | Balanced Monte-Carlo resampling strategy
binning | Spectral data binning
bline | Baseline Correction for Spectral Data
calibrate | Chemical Shift Calibration
cliffs_d | Cliff's Delta Effect Size
correct_baseline | Baseline Correction for Spectral Data
correct_lw | Linewidth correction by scaling spectra to a reference linewidth
covid | COVID-19 blood plasma proton NMR spectra (processed)
covid_raw | COVID-19 blood plasma proton NMR spectra (raw)
cv_anova | Cross-validated ANOVA for O-PLS models
dmodx | Distance to the Model in X-Space (DModX)
ellipse2d | Calculate 2D Hotelling T^2 Ellipse
es_cdelta | Cliff's Delta Effect Size
excise | Excise Chemical Shift Regions from 1D NMR Spectra
fitted | Extract fitted Y values
fitted-method | Extract fitted Y values
get.idx | Select Indices for a Chemical Shift Region
get_idx | Select Indices for a Chemical Shift Region
get_provenance | Retrieve metabom8 provenance metadata
hiit_raw | High-intensity interval training (HIIT) 1H NMR urine dataset
hotellingsT2 | Hotelling T^2 Statistic
kfold | K-fold cross-validation strategy
list_preprocessing | List available preprocessing steps
loadings-method | Model loadings
lw | Full Width at Half Maximum (FWHM) Estimation
m8_model | m8_model class Model object returned by 'pca()', 'pls()', and 'opls()'.
m8_model-class | m8_model class Model object returned by 'pca()', 'pls()', and 'opls()'.
matspec | Plot 1D NMR Spectra
mc | Monte-Carlo cross-validation strategy
metabom8 | metabom8: A High-Performance R Package for Metabolomics Modeling and Analysis
minmax | Min-Max Scaling to [0,1]
noise_sd | Estimate Noise Standard Deviation in 1D NMR Spectra
norm_eretic | Normalise Spectra Using ERETIC Signal
opls | Fit an Orthogonal Partial Least Squares (O-PLS) model
opls_perm | OPLS Model Validation via Y-Permutation
pareto_scaling | Pareto Scaling Leaves variables unscaled. Optional centering.
pca | Principal Component Analysis (PCA)
plotStocsy | Plot STOCSY result
plot_spec | Plot 1D NMR Spectra
pls | Fit a Partial Least Squares (PLS) model
ppick | Find Local Extrema in NMR Spectra (Peak Picking)
ppick2 | Peak picking using Savitzky–Golay derivatives
pqn | Probabilistic Quotient Normalisation (PQN)
prep_X | Applies a preprocessing strategy to a numeric matrix.
print_preprocessing | List available preprocessing functions Returns the preprocessing utilities provided by 'metabom8'.
print_provenance | Print metabom8 preprocessing pipeline
read1d | Import 1D NMR spectra (TopSpin processed)
read1d_proc | Import 1D NMR spectra (TopSpin processed)
read1d_raw | Read raw FIDs and process to spectra
scores | PLS/OPLS model scores
scores-method | PLS/OPLS model scores
scRange | Min-Max Scaling to Arbitrary Range
show-method | m8_model class Model object returned by 'pca()', 'pls()', and 'opls()'.
spec | Plot 1D NMR Spectra
stocsy | Statistical Total Correlation Spectroscopy (STOCSY)
storm | Subset Optimisation by Reference Matching (STORM)
stratified_kfold | Y-stratified k-fold cross-validation strategy
summary-method | m8_model class Model object returned by 'pca()', 'pls()', and 'opls()'.
unscaled | No Scaling This function defines a preprocessing strategy that is applied via 'prep_X'.
uv_scaling | Unit Variance Scaling This function defines a preprocessing strategy that is applied via 'prep_X'.
vip | Variable Importance in Projection (VIP)
vip-method | Variable Importance in Projection (VIP)
weights | Extract model weights
weights-method | Extract model weights
xres | Compute X residual matrix Returns the residual matrix (E) of an OPLS model.
xres-method | Compute X residual matrix Returns the residual matrix (E) of an OPLS model.