A multiway approach to data integration in systems biology based on Tucker3 and N-PLS

被引:25
作者
Conesa, Ana [1 ]
Prats-Montalban, Jose M. [2 ]
Tarazona, Sonia [1 ,2 ]
Jose Nueda, Ma [3 ]
Ferrer, Alberto [2 ]
机构
[1] Ctr Invest Principe Felipe, Bioinformat & Genom Dept, Valencia, Spain
[2] Univ Politecn Valencia, Dept Estadist & Invest Operat Aplicadas & Calidad, Valencia, Spain
[3] Univ Alicante, Dept Estadist & Invest Operat, Alicante, Spain
关键词
Multi-way analysis; N-PLS; Tucker3; Data integration; Omics data; Systems biology; PRINCIPAL COMPONENT ANALYSIS; GENE-EXPRESSION; TRANSCRIPT; METABOLOMICS; BIOSYNTHESIS; PROFILES; NETWORKS; ASCA; TOOL;
D O I
10.1016/j.chemolab.2010.06.004
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper discusses the potential of multi-way projection methods for analysing multifactorial data structures to identify underlying components of variability that interconnect different blocks of omics variables. We explore their suitability for explorative and variable selection analysis of systems biology data where different types of biological parameters are studied together. These methodologies were applied to the integrative analysis of a functional genomics dataset where transcriptomics, metabolomics and physiological data are available. Our results show that multiway methods are suited to accommodate multifactorial omics experiments and to analyse relationships between different biochemical layers. Additionally, strategies are presented for variable selection in the context of omics data and for interpreting results at the level of cellular pathways. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:101 / 111
页数:11
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