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ChemPhys.md

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ChemPhys
Chemometrics and Computational Physics
Katharine Mullen
2024-01-29

Chemometrics and computational physics are concerned with the analysis of data arising in chemistry and physics experiments, as well as the simulation of physico-chemico systems. Many of the functions in base R are useful for these ends.

The second edition of Chemometrics with R: Multivariate Data Analysis in the Natural and Life Sciences by Ron Wehrens, ISBN 978-3-662-62027-4, Springer, 2020, provides an introduction to multivariate statistics in the life sciences, as well as coverage of several specific topics from the area of chemometrics. The associated package r github("rwehrens/ChemometricsWithR") facilitates reproduction of the examples in the book.

The book Modern Statistical Methods for Astronomy With R Applications by Eric D. Feigelson and G. Jogesh Babu, ISBN-13: 9780521767279, Cambridge, 2012, provides an introduction to statistics for astronomers and an overview of the foremost methods being used in astrostatistical analysis, illustrated by examples in R.

The book by Kurt Varmuza and Peter Filzmoser, Introduction to Multivariate Statistical Analysis in Chemometrics, ISBN 978-1-420-05947-2, CRC Press, 2009, is associated with the package r pkg("chemometrics").

A special issue of R News with a focus on R in Chemistry was published in August 2006. A special volume of Journal of Statistical Software (JSS) dedicated to Spectroscopy and Chemometrics in R was published in January 2007.

Please e-mail the maintainer, submit an issue or pull request in the GitHub repository linked above, if we have omitted something of importance, or if a new package or function should be mentioned here.

Linear Regression Models

  • Linear models can be fitted (via OLS) with lm() (from stats). A least squares solution for x in Ax = b can also be computed as qr.coef(qr(A), b).
  • The package r pkg("nnls", priority = "core") provides a means of constraining x to non-negative or non-positive values; the package r pkg("bvls") allows other bounds on x to be applied.
  • Functions for isotonic regression are available in the package r pkg("Iso", priority = "core"), and are useful to determine the unimodal vector that is closest to a given vector x under least squares criteria.
  • Heteroskedastic linear models can be fit using the gls() function of the r pkg("nlme") package.

Nonlinear Regression Models

  • The nls() function (from stats) as well as the package r pkg("minpack.lm") allow the solution of nonlinear least squares problems.
  • Correlated and/or unequal variances can be modeled using the gnls() function of the r pkg("nlme") package and by r pkg("nlreg").

Curve Resolution

  • The r pkg("PTAk", priority = "core") package provides functions for Principal Tensor Analysis on k modes. The package includes also some other multiway methods: PCAn (Tucker-n) and PARAFAC/CANDECOMP.
  • Multivariate curve resolution alternating least squares (MCR-ALS) is implemented in the package r pkg("ALS", priority = "core").
  • The r bioc("alsace") package provides MCR-ALS support for Liquid chromatography with PhotoDiode Array Detection (LC-DAD) data with many injections, with features for peak alignment and identification.
  • The package r pkg("drc") provides functions for the analysis of one or multiple non-linear curves with focus on models for concentration-response, dose-response and time-response data.
  • The package r pkg("mdatools") provides functions for MCR-ALS with constraints and a purity based methods similar to SIMPLISMA.
  • The r pkg("albatross") package specialises in non-negative Parallel Factor Analysis of fluorescence excitation-emission matrices and provides auxillary functions relevant to analysis of natural waters.

Partial Least Squares

  • The package r pkg("pls", priority = "core") implements Partial Least Squares Regression (PLSR) and Principal Component Regression (PCR).
  • The package r pkg("lspls") implements the least squares-partial least squares (LS-PLS) method.
  • Sparse PLS is implemented in the package r pkg("spls") package.
  • The r bioc("gpls") package implements generalized partial least squares, based on the Iteratively ReWeighted Least Squares (IRWLS) method of Brian Marx.
  • The package r pkg("enpls") implements ensemble partial least squares, a framework for measuring feature importance, outlier detection, and ensemble modeling based on (sparse) partial least squares regressions.
  • The package r pkg("mdatools") provides functions for both PLS regression and discriminant analysis (PLSDA), including numerous plots, Jack-Knifing inference for regression coefficients and many other supplementary tools.

Principal Component Analysis

  • Principal component analysis (PCA) is in the package stats as functions princomp(). Some graphical PCA representations can be found in the r pkg("psy") package.
  • The r pkg("homals") package provides nonlinear PCA and, by defining sets, nonlinear canonical correlation analysis (models of the Gifi-family).
  • A desired number of robust principal components can be computed with the r pkg("pcaPP") package. The package r pkg("elasticnet") is applicable to sparse PCA.
  • The package r pkg("mdatools") provides functions for PCA analysis. The functions work both with conventional datasets as well as with images, including spectral images. A randomized version of PCA can be used to speed up calculations for large datasets. The package also implements PCA based classification method, Soft Independent Modelling of Class Analogy (SIMCA).
  • The package r pkg("pcv") implements the Procrustes cross-validation method for PCA, Principal Component Regression and Partial Least Squares regression models.
  • The r pkg("LearnPCA") package provides a series of vignettes explaining PCA.

Factor Analysis

  • Factor analysis (FA) is in the package stats as functions factanal(); see r view("Psychometrics") task view for details on extensions.

Compositional Data Analysis

  • The package r pkg("compositions") provides functions for the consistent analysis of compositional data (e.g. portions of substances) and positive numbers (e.g. concentrations). See also the book, Analyzing Compositional Data with R by K. Gerald von den Boogaart und Raimon Tolosana-Delgado, ISBN: 978-3-642-36808-0, Springer, 2013.

Independent Component Analysis

  • Independent component analysis (ICA) can be computed using r pkg("fastICA").

Clustering

  • The r view("Cluster") task view provides a list of packages that can be used for clustering problems.

Variable Selection

  • Stepwise variable selection for linear models, using AIC, is available in function step(); package r pkg("leaps") implements leaps-and-bounds variable selection, by default using Mallow's Cp. r pkg("stepPlr") provides stepwise variable selection for penalized logistic regression.
  • Package r pkg("varSelRF") provides variable selection methods for random forests. Package r pkg("clustvarsel") implements variable selection for model-based clustering.
  • The r pkg("BioMark") package implements two meta-methods for variable selection: stability selection (applying a primary selection method like a t-test, VIP value or PLSDA regression coefficient) to different subsets of the data, and higher criticism, which provides a data-driven choice of significance cutoffs in statistical testing.
  • The package r pkg("mdatools") implements methods based on VIP scores, Selectivity Ratio (SR) as well as interval PLS.

Self-Organizing Maps

  • The r pkg("kohonen", priority = "core") package implements self-organizing maps as well as some extensions for supervised pattern recognition and data fusion. The r pkg("som") package provides functions for self-organizing maps.

Differential Equations

  • See the r view("DifferentialEquations") task view packages dealing with differential equations.

Metrology

  • The r pkg("units") package attaches unit metadata to vectors, matrices and arrays, providing automatic propagation, conversion, derivation and simplification of units.
  • The r pkg("errors") package attaches uncertainty metadata to vectors, matrices and arrays, providing automatic propagation and reporting.
  • The r pkg("quantities") package integrates the packages r pkg("units") and r pkg("errors") to provide a quantity calculus system for vectors, matrices and arrays.
  • The r pkg("constants") package provides values of the fundamental physical constants based on values reported by the Committee on Data for Science and Technology (CODATA), an interdisciplinary committee of the International Council for Science.
  • r pkg("NISTunits") also provides values of the fundamental physical constants. The values it contains are based on the values reported by the National Institute of Standards and Technology, (NIST).
  • r pkg("measurements") contains tools to make working with physical measurements easier, such as functions to convert between metric and imperial units, or to calculate a dimension's unknown value from other dimensions' measurements.
  • The r pkg("metRology") package provides support for metrology applications, including measurement uncertainty estimation and inter-laboratory metrology comparison studies.

Calibration

  • The r pkg("investr") package facilitates calibration/inverse estimation with linear and nonlinear regression models.
  • The r pkg("chemCal", priority = "core") package provides functions for plotting linear calibration functions and estimating standard errors for measurements.
  • The r pkg("nlreg") package is useful for nonlinear calibration models.

Cellular Automata

  • The r pkg("simecol") package includes functions for cellular automata modeling.

Thermodynamics

  • The r pkg("CHNOSZ") package provides functions for calculating the standard Gibbs energies and other thermodynamic properties, and chemical affinities of reactions between species contained in a thermodynamic database.
  • The r pkg("IAPWS95") package provides functions to calculate the thermodynamic properties of water according to the International Association for the Properties of Water and Steam (IAPWS) 1995 formulations.

Interfaces to External Libraries

  • The package r pkg("rcdk") allows the user to access functionality in the Chemistry Development Kit (CDK), a Java framework for cheminformatics. This allows the user to load molecules, evaluate fingerprints (via the package r pkg("fingerprint")), calculate molecular descriptors and so on. In addition, the CDK API allows the user to view structures in 2D. The r pkg("rcdklibs") package provides the CDK libraries for use in R.
  • r bioc("ChemmineR") is a cheminformatics toolkit for analyzing small molecules in R. Its add-on packages include r bioc("fmcsR") for mismatch tolerant maximum common substructure matching, r bioc("eiR") for accelerated structure similarity searching; r bioc("bioassayR") for analyzing bioactivity data, and r bioc("ChemmineOB") for accessing OpenBabel functionalities from R.
  • The r pkg("webchem") package allows users to retrieve chemical information from various sources on the web and to interact with various APIs. Sources include: Chemical Identifier Resolver, ChemSpider, PubChem, Chemical Translation Service, PAN Pesticide Database, Alan Wood's Compendium of Pesticide Common Names, PHYSPROP Database, ETOX, PPDB, and ChemIDplus.
  • The package r pkg("standartox") allows the user to access the Standartox database of ecotoxicological test data.

Spectroscopy

  • Bryan Hanson has compiled a broad range of Free and Open Source Software (FOSS) for Spectroscopy, much of which is in the form of R packages.
  • The r pkg("spectralAnalysis") package allows users to pre-process, visualize and analyze spectroscopy data. Non-negative matrix factorization analysis is included.
  • The r pkg("ChemoSpec") package collects user-friendly functions for plotting spectra (NMR, IR, etc) and carrying top-down exploratory data analysis, such as HCA, PCA and model-based clustering.
  • The r github("Chathurga/HyperChemoBridge") interconverts r pkg("ChemoSpec") (and hyperSpec) objects
  • The r pkg("speaq") package implements the hierarchical Cluster-based Peak Alignment (CluPA) and may be used for aligning NMR spectra.
  • The package r pkg("TIMP") provides a problem solving environment for fitting separable nonlinear models in physics and chemistry applications, and has been extensively applied to time-resolved spectroscopy data.
  • The package r pkg("ChemoSpec2D") allows exploratory chemometrics of 2D spectroscopic data sets such as COSY (correlated spectroscopy) and HSQC (heteronuclear single quantum coherence) 2D NMR (nuclear magnetic resonance) spectra.
  • The r pkg("spectrino") package provides tools for spectra viewing and organization.
  • The r pkg("NIRStat") package provides transfusion-related differential tests on near-infrared spectroscopy (NIRS) time series.
  • The r pkg("serrsBayes") package allows Bayesian modeling of raman spectroscopy data.
  • The r pkg("ir") package performs IR data analysis functions (such as baseline correction, binning, clipping, interpolating, smoothing, averaging, adding, subtracting, dividing, multiplying, plotting).
  • The r pkg("PlotFTIR") package easily produces journal-quality IR spectral graphics using r pkg("ggplot2") and interfaces with r pkg("ir") and r pkg("ChemoSpec").

Chromatography

  • r pkg("chromConverter") provides parsers to read chromatographic data into R. It can work with a wide range of formats.
  • r pkg("GCalignR") aligns peaks based on peak retention times and matches homologous peaks across samples.
  • The r pkg("LCMSQA") package provides tools to check the quality of liquid chromatograph/mass spectrometry (LC/MS) experiments.
  • r pkg("RGCxGC") is a toolbox for the analysis of bidimensional gas chromatography data.
  • The r pkg("RpeakChrom") package contains tools for chromatographic column characterization and modeling chromatographic peaks.

Mass Spectrometry

  • r bioc("MSnbase") defines infrastructure for mass spectrometry-based proteomics data handling, plotting, processing and quantification.
  • r pkg("MALDIquant") provides tools for quantitative analysis of MALDI-TOF mass spectrometry data, with support for baseline correction, peak detection and plotting of mass spectra. r pkg("MALDIquantForeign") imports data into/from 'MALDIquant' objects.
  • The r pkg("OrgMassSpecR") package is for organic/biological mass spectrometry, with a focus on graphical display, quantification using stable isotope dilution, and protein hydrogen/deuterium exchange experiments.
  • The Bioconductor packages r bioc("MassSpecWavelet"), r bioc("PROcess"), and r bioc("xcms") are designed for the analysis of mass spectrometry data.
  • The apLCMS package is designed for the processing of LC/MS based metabolomics data.
  • The xMSanalyzer package allows merging apLCMS sample processing results from multiple sets of parameter settings, among other features.
  • The MSPrep package is for post-processing of metabolomic data, including summarization of replicates, filtering, imputation, and normalization.
  • The r bioc("metaMS") package is an MS-based metabolomics data processing and compound annotation pipeline.
  • The r pkg("RaMS") package reads in mzML and mzXML files as r pkg("data.table") objects for visualization and data manipulation with the r pkg("tidyverse").
  • r pkg("readMzXmlData") imports data in the mzXML format.
  • r pkg("readBrukerFlexData") imports data in the Bruker *flex format.
  • r pkg("MSbox") provides a suite of tools for mass spectrometry data analysis.
  • r pkg("enviPat") allows isotope pattern, profile and centroid calculation for mass spectrometry.
  • r pkg("HaDeX") provides functions for processing, analysis and visualization of Hydrogen Deuterium eXchange monitored by Mass Spectrometry experiments (HDX-MS).
  • r pkg("accucor") implements an isotope natural abundance correction algorithm that is needed especially for high resolution mass spectrometers.

Magnetic Resonance Imaging, Magnetic Resonance Spectroscopy

  • The r view("MedicalImaging") task view provides a list of packages that can be used on fMRI, MRI, and related data.

Fluorescence Lifetime Imaging Microscopy

  • Functions for visualization and analysis of Fluorescence Lifetime Imaging Microscopy (FLIM) datasets are available in the package r pkg("TIMP").

Carbon Dating

  • The package r pkg("Bchron") creates chronologies based on radiocarbon and non-radiocarbon dated depths.
  • The package r pkg("rcarbon") enables the calibration and analysis of radiocarbon dates.
  • The package r pkg("ISRaD") provides data and tools for the development, maintenance, analysis, and deployment of the International Soil Radiocarbon Database (ISRaD).
  • The package r pkg("nimbleCarbon") provides functions for Bayesian analyses of radiocarbon dates.
  • The package r pkg("rcarbon") enables the calibration and analysis of radiocarbon dates.
  • The package r pkg("spDates") allows analysis of spatial gradients in radiocarbon dates.

Astronomy and Astrophysics

  • The r pkg("astrodatR") package collects 19 datasets from contemporary astronomy research, many of which are described in the aforementioned textbook 'Modern Statistical Methods for Astronomy with R Applications'.
  • The r pkg("RobPer") package calculates periodograms based on (robustly) fitting periodic functions to light curves.
  • The package r pkg("snapshot") contains functions for reading and writing N-body snapshots from the GADGET code for cosmological N-body/SPH simulations.
  • The r pkg("solaR") package provides functions to determine the movement of the sun from the earth and to determine incident solar radiation.
  • The r pkg("FITSio") package provides utilities to read and write files in the FITS (Flexible Image Transport System) format, a standard format in astronomy.
  • The r pkg("stellaR") package manages and displays stellar tracks and isochrones from the Pisa low-mass database.
  • The r pkg("astroFns") package provides miscellaneous astronomy functions, utilities, and data.
  • The r pkg("cosmoFns") package contains standard expressions for distances, times, luminosities, and other quantities useful in observational cosmology, including molecular line observations.
  • The r pkg("celestial") package includes a number of common astronomy conversion routines, particularly the HMS and degrees schemes.
  • The r pkg("SCEPtER") package is used to estimate stellar mass and radius given observational data of effective temperature, [Fe/H], and astroseismic parameters.
  • The r pkg("lira") package performs Bayesian linear regression and forecasting in Astronomy, accounting for all kinds of errors and correlations in the data.
  • The r pkg("SPADAR") package provides functions to create all-sky grid plots of widely used astronomical coordinate systems (equatorial, ecliptic, galactic) and scatter plots of data on any of these systems, including on-the-fly system conversion.
  • The r pkg("SCEPtERbinary") package allows for estimating the stellar age for double-lined detached binary systems, adopted from the effective temperature, the metallicity [Fe/H], the mass, and the radius of the two stars.
  • The r pkg("panstarrs") package contains a data archive of the PS1 wide-field astronomical survey, and can be used to plan astronomical observations, make guidance pictures, and find magnitudes in five broadband filters.
  • The r pkg("lorentz") package performs the Lorentz transformations of special relativity. Active and passive transforms are implemented. It includes functionality for the gyrogroup structure of three-velocities.
  • The Astrostatistics and Astroinformatics Portal is an R-centric collection of information regarding statistical analysis in astronomy.
  • Hans Werner Borchers has a page on Astronomy modules and links for R, Python, and Julia.

Energy Modeling

  • The r pkg("solaR") package provides functions to simulate and model systems involved in the capture and use of solar energy, including photovoltaics.

Water and Soil Chemistry

  • The r pkg("AquaEnv") package is a toolbox for aquatic chemical modelling focused on (ocean) acidification and CO2 air-water exchange.
  • See the r view("Environmetrics") task view for further related packages related to water and soil chemistry.

Titration Curves

  • The r pkg("titrationCurves") package provides functions to plot acid/base, complexation, redox, and precipitation titration curves.

Electrochemistry

  • The r pkg("eChem") package provides functions to simulate voltammetry, chronoamperometry and chronocoulometry experiments, which may be useful in courses in analytical chemistry.

Health Physics

  • The package r pkg("radsafer") provides functions for radiation safety; the package r pkg("RadData") provides nuclear decay data for dosimetric calculations from the International Commission on Radiological Protection.
  • The package r pkg("AeroSampleR") allows estimation of ideal efficiencies of aerosol sampling.

Links