BALZARINI MONICA GRACIELA
Artículos
Título:
lmdme: Linear Model on Designed Multivariate Experiments in R.
Autor/es:
FRESNO, C.; BALZARINI, M.; FERNANDEZ, E.
Revista:
JOURNAL OF STATISTICAL SOFTWARE
Editorial:
JOURNAL STATISTICAL SOFTWARE
Referencias:
Año: 2014 vol. 56 p. 1 - 1
ISSN:
1548-7660
Resumen:
he lmdme package implements analysis of variance (ANOVA) decomposition through linear models on designed multivariate experiments in R (R Development Core Team 2012), allowing ANOVA-principal component analysis (APCA) and ANOVA-simultaneous component analysis (ASCA). It also extends both methods with the application of partial least squares (PLS) through the specication of a desired output matrix. The package is freely available on the Bioconductor website (Gentleman et al. 2004), licenced under GNU general public license. ANOVA decomposition methods for multivariate designed experiments are becoming popular in omics" experiments (transcriptomics, metabolomics, etc.) where measure-ments are performed according to a predened experimental design (Smilde et al. 2005), with several experimental factors or including subject specic clinical covariates, such as those present in current clinical genomic studies. ANOVA-PCA and ASCA are well-suited methods to study interaction patterns on mult