4.6 Article

staRdom: Versatile Software for Analyzing Spectroscopic Data of Dissolved Organic Matter in R

Journal

WATER
Volume 11, Issue 11, Pages -

Publisher

MDPI
DOI: 10.3390/w11112366

Keywords

dissolved organic matter; DOM; PARAFAC; R; spectroscopy; fluorescence; absorbance; EEM; peak picking; drEEM; staRdom

Funding

  1. Provincial Government of Lower Austria, No Forschungs- und Bildungs GmbH, within the Science Call 2015 [SC15-002]
  2. Swedish Research Council [FORMAS 2017-00743]
  3. doctoral school Human River Systems in the 21st century (HR21)

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The roles of dissolved organic matter (DOM) in microbial processes and nutrient cycles depend on its composition, which requires detailed measurements and analyses. We introduce a package for R, called staRdom (spectroscopic analysis of DOM in R), to analyze DOM spectroscopic data (absorbance and fluorescence), which is key to deliver fast insight into DOM composition of many samples. staRdom provides functions that standardize data preparation and analysis of spectroscopic data and are inspired by practical work. The user can perform blank subtraction, dilution correction, Raman normalization, scatter removal and interpolation, and fluorescence normalization. The software performs parallel factor analysis (PARAFAC) of excitation-emission matrices (EEMs), including peak picking of EEMs, and calculates fluorescence indices, absorbance indices, and absorbance slope indices from EEMs and absorbance spectra. A comparison between PARAFAC solutions by staRdom in R compared with drEEM in MATLAB showed nearly identical solutions for most datasets, although different convergence criteria are needed to obtain similar results and interpolation of missing data is important when working with staRdom. In conclusion, staRdom offers the opportunity for standardized multivariate decomposition of spectroscopic data without requiring software licensing fees and presuming only basic R knowledge.

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