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Group-wise ANOVA simultaneous component analysis for designed omics experiments

Edoardo Saccenti; Age k. Smilde; José Camacho
Abstract:
Modern omics experiments pertain not only to the measurement of many variables but also follow complex experimental designs where many factors are manipulated at the same time. This data can be conveniently analyzed using multivariate tools like ANOVA-simultaneous component analysis (ASCA) which allows interpretation of the variation induced by the different factors in a principal component analysis fashion. However, while in general only a subset of the measured variables may be related to the problem studied, all variables contribute to the final model and this may hamper interpretation.
Research areas:
Year:
2018
Type of Publication:
Article
Keywords:
Analysis of variance; Designed experiments; Principal component analysis; Sparsity
Journal:
Metabolomics
Volume:
14
Number:
6
Pages:
63
Month:
May
DOI:
10.1007/s11306-018-1369-1
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