albatross-package {albatross}

PARAFAC Analysis of Fluorescence Excitation-Emission Matrices

Description

Day after day, day after day,
We stuck, nor breath nor motion;
As idle as a painted ship
Upon a painted ocean.

Water, water, every where,
And all the boards did shrink;
Water, water, every where,
Nor any drop to drink.

– Samuel Taylor Coleridge, The Rime of the Ancient Mariner

Perform parallel factor analysis (PARAFAC: Hitchcock, 1927) <doi:10.1002/sapm192761164> 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.

Details

In order to work with your data, create feem and/or feemcube objects from files or matrix or array objects. Use feemlist to import files in bulk. If your files aren't in one of the formats supported by feem but you can read their contents by other means, you can supply an importer function to feemlist; it should take a file name and return the corresponding feem object.

Operations that can be performed on the objects include plotting (plot.feem), calculation of fluorescence indices (feemindex), inner-filter effect correction (feemife), handling of scattering signal (feemscatter), changing the wavelength grid of the data by means of interpolation (feemgrid), and scaling (feemscale). Scaling may be automatically undone after performing the PARAFAC decomposition so that the resulting scores would correspond to the data as it was before the scaling.

All processing functions can take individual feem objects, lists of them, or feemcube objects and return values of the appropriate kind. For example, feemscatter always returns an object of the same class but with the scattering signal handled, while feemindex returns named numeric vectors for individual feems but data.frames for collections of them. There's a slight memory benefit to using lists of feem objects, but the difference shouldn't be noticeable, so there's nothing to worry about if you started with a feemcube.

In order to compute PARAFAC, you need to convert your data into a feemcube. Whether you perform jack-knifing, split-half analysis, or PARAFAC itself, a copy of the data cube is kept together with the results and can be extracted back using the feemcube function. The resulting objects support a plot method (described in the same help page) and can give you the data as a few-column data.frame using the coef method.

Once the analysis is finished, the PARAFAC model can be exported for the OpenFluor database (write.openfluor) or stored as an R object using standard R tools (save or saveRDS).

Index of help topics:

[.feem                  Extract or replace parts of FEEM objects
[.feemcube              Extract or replace parts of FEEM cubes
absindex                Functions of absorbance data
albatross-package       PARAFAC Analysis of Fluorescence
                        Excitation-Emission Matrices
as.data.frame.feem      Transform a FEEM object into a data.frame
feem                    Create a fluorescence excitation-emission
                        matrix object
feemcorcondia           Core consistency diagnostic for PARAFAC models
feemcube                Data cubes of fluorescence excitation-emission
                        matrices
feemflame               Fluorescence and scAttering Model Estimation
feemgrid                Interpolate FEEMs on a given wavelength grid
feemife                 Absorbance-based inner filter effect correction
feemindex               Fluorescence indices and peak values
feemjackknife           Jack-knife outlier detection in PARAFAC models
feemlist                Create lists of FEEM objects
feemparafac             Compute PARAFAC on a FEEM cube object and
                        access the results
feems                   Synthetic fluorescence excitation-emission
                        matrices and absorbance spectra
feemscale               Rescale FEEM spectra to a given norm and
                        remember the scale factor
feemscatter             Handle scattering signal in FEEMs
feemsplithalf           Split-half analysis of PARAFAC models
marine.colours          Perceptually uniform palettes
plot.feem               Plot a FEEM object
write.openfluor         Export a PARAFAC model for the OpenFluor
                        database

Author(s)

Ivan Krylov [aut, cre], Timur Labutin [ths], Anastasia Drozdova [rev]

References

Murphy KR, Stedmon CA, Graeber D, Bro R (2013). “Fluorescence spectroscopy and multi-way techniques. PARAFAC.” Analytical Methods, 5, 6557-6566. doi:10.1039/c3ay41160e.

Pucher M, Wünsch U, Weigelhofer G, Murphy K, Hein T, Graeber D (2019). “staRdom: Versatile Software for Analyzing Spectroscopic Data of Dissolved Organic Matter in R.” Water, 11(11), 2366. doi:10.3390/w11112366.

Cleese J, Jones T (1970). “Albatross: Flavours of different sea birds.” Journal of Flying Circus, 1.13, 7:05-7:45.

Krylov I, Drozdova A, Labutin T (2020). “Albatross R package to study PARAFAC components of DOM fluorescence from mixing zones of arctic shelf seas.” Chemometrics and Intelligent Laboratory Systems, 207(104176). doi:10.1016/j.chemolab.2020.104176.

See Also

feem, feemlist, feemindex, feemife, feemscatter, feemgrid, feemcube, feemscale, feemsplithalf, feemparafac, feemjackknife, feemflame, absindex.

Examples

  data(feems)

  dataset <- feemcube(feems, FALSE)
  dataset <- feemscatter(dataset, c(24, 15, 10), 'whittaker')
  dataset <- feemife(dataset, absorp)
  plot(dataset <- feemscale(dataset, na.rm = TRUE))

  
    # takes a long time
    (sh <- feemsplithalf(
      feemscatter(cube, c(24, 15)),
      # in real life, set a stricter stopping criterion, 1e-6..1e-8
      nfac = 2:4, splits = 4, ctol = 1e-4
    ))
    plot(sh)
  

  pf <- feemparafac(cube, nfac = 3, ctol = 1e-4)
  plot(pf)