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albatross (version 0.3-8)

PARAFAC Analysis of Fluorescence Excitation-Emission Matrices

Description

Perform parallel factor analysis (PARAFAC: Hitchcock, 1927) on fluorescence excitation-emission matrices: handle scattering signal and inner filter effect, scale the dataset, fit the model; perform split-half validation or jack-knifing. Modified approaches such as Whittaker interpolation, randomised split-half, and fluorescence and scattering model estimation are also available. The package has a low dependency footprint and has been tested on a wide range of R versions.

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Version

Install

install.packages('albatross')

Monthly Downloads

397

Version

0.3-8

License

GPL (>= 3)

Maintainer

Ivan Krylov

Last Published

May 7th, 2024

Functions in albatross (0.3-8)

Implementation notes for constrained matrix factorisation

Functions of absorbance data

Extract or replace parts of FEEM objects

as.data.frame.feem

Transform a FEEM object into a data.frame

Data cubes of fluorescence excitation-emission matrices

Fluorescence and scAttering Model Estimation

Create a fluorescence excitation-emission matrix object

albatross-package

tools:::Rd_package_title("albatross")

Core consistency diagnostic for PARAFAC models

Extract or replace parts of FEEM cubes

Create lists of FEEM objects

Interpolate FEEMs on a given wavelength grid

Synthetic fluorescence excitation-emission matrices and absorbance spectra

Compute PARAFAC on a FEEM cube object and access the results

Fluorescence indices and peak values

Split-half analysis of PARAFAC models

Absorbance-based inner filter effect correction

Rescale FEEM spectra to a given norm and remember the scale factor

Handle scattering signal in FEEMs

Jack-knife outlier detection in PARAFAC models

Perceptually uniform palettes

Plot a FEEM object

Implementation notes for Whittaker smoothing and interpolation of surfaces

write.openfluor

Export a PARAFAC model for the OpenFluor database