title: Partial Least Squares with Structured Output for Modelling the Metabolomics Data Obtained from Complex Experimental Designs: A Study into the Y-Block Coding.
abstract: Partial least squares (PLS) is one of the most commonly used supervised modelling approaches for analysing multivariate metabolomics data. PLS is typically employed as either a regression model (PLS-R) or a classification model (PLS-DA). However, in metabolomics studies it is common to investigate multiple, potentially interacting, factors simultaneously following a specific experimental design. Such data often cannot be considered as a "pure" regression or a classification problem. Nevertheless, these data have often still been treated as a regression or classification problem and this could lead to ambiguous results. In this study, we investigated the feasibility of designing a hybrid target matrixYthat better reflects the experimental design than simple regression or binary class membership coding commonly used in PLS modelling. The new design ofYcoding was based on the same principle used by structural modelling in machine learning techniques. Two real metabolomics datasets were used as examples to illustrate how the newYcoding can improve the interpretability of the PLS model compared to classic regression/classification coding.
authors: School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester M1 7DN, UK. yun.xu-2@manchester.ac.uk.
authors: Yun
authors: Y
authors: Xu
authors: School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester M1 7DN, UK. howbeer.muhamadali@manchester.ac.uk.
authors: Howbeer
authors: H
authors: Muhamadali
authors: School of Chemistry, Umm Al-Qura University, Al Taif Road, Mecca 24382, Saudi Arabia. aasayqal@uqu.edu.sa.
authors: Ali
authors: A
authors: Sayqal
authors: School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester M1 7DN, UK. Neil.Dixon@manchester.ac.uk.
authors: Neil
authors: N
authors: Dixon
authors: School of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, Manchester M1 7DN, UK. roy.goodacre@manchester.ac.uk.
authors: Royston
authors: R
authors: Goodacre
keywords: Y coding; experimental design; metabolomics; partial least squares; structural modelling