Chemometrics in foodomics: handling data structures from multiple analytical platforms

TY - JOUR

T1 - Chemometrics in foodomics

T2 - handling data structures from multiple analytical platforms

AU - Skov, Thomas

AU - Honoré, Anders Hans

AU - Jensen, Henrik Max

AU - Næs, Tormod

AU - Engelsen, Søren Balling

PY - 2014/9/1

Y1 - 2014/9/1

N2 - Foodomics studies are normally concerned with multifactorial problems and it makes good sense to explore and to measure the same samples on complementary, synergistic analytical platforms that comprise multifactorial sensors and separation methods. However, the challenge of exploring, extracting and describing the data increases exponentially. Moreover, the risk of becoming flooded with non-informative data increases concomitantly. Acquisition of data from different analytical platforms provides opportunities for checking the validity of the data, comparing analytical platforms and ensuring proper data (pre)processing - all in the context of correlation studies. We provide practical and pragmatic tools to validate and to deal advantageously with data from more than one analytical platform. We emphasize the need for complementary correlation studies within and between blocks of data to ensure proper data handling, interpretation and dissemination. Correlation studies are a preliminary step prior to multivariate data analysis or as an introduction to more advanced multi-block methods.

AB - Foodomics studies are normally concerned with multifactorial problems and it makes good sense to explore and to measure the same samples on complementary, synergistic analytical platforms that comprise multifactorial sensors and separation methods. However, the challenge of exploring, extracting and describing the data increases exponentially. Moreover, the risk of becoming flooded with non-informative data increases concomitantly. Acquisition of data from different analytical platforms provides opportunities for checking the validity of the data, comparing analytical platforms and ensuring proper data (pre)processing - all in the context of correlation studies. We provide practical and pragmatic tools to validate and to deal advantageously with data from more than one analytical platform. We emphasize the need for complementary correlation studies within and between blocks of data to ensure proper data handling, interpretation and dissemination. Correlation studies are a preliminary step prior to multivariate data analysis or as an introduction to more advanced multi-block methods.

U2 - 10.1016/j.trac.2014.05.004

DO - 10.1016/j.trac.2014.05.004

M3 - Journal article

SN - 0165-9936

VL - 60

SP - 71

EP - 79

JO - Trends in Analytical Chemistry

JF - Trends in Analytical Chemistry

ER -