A High-Performance R Package for Metabolomics Modeling and Analysis

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Documentation for package ‘metabom8’ version 0.99.10

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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.