lmdme: Linear Models on Designed Multivariate Experiments in R

Cristóbal Fresno, Mónica Balzarini and Elmer Fernández

Journal of Statistical Software, 2014, vol. 056, issue i07

Abstract: The lmdme package decomposes analysis of variance (ANOVA) through linear models on designed multivariate experiments, allowing ANOVA-principal component analysis (APCA) and ANOVA-simultaneous component analysis (ASCA) in R. It also extends both methods with the application of partial least squares (PLS) through the specification of a desired output matrix. The package is freely available from Bioconductor and licensed under the GNU General Public License.ANOVA decomposition methods for designed multivariate experiments are becoming popular in “omics” experiments (transcriptomics, metabolomics, etc.), where measurements are performed according to a predefined experimental design, with several experimental factors or including subject-specific clinical covariates, such as those present in current clinical genomic studies. ANOVA-PCA and ASCA are well-suited methods for studying interaction patterns on multidimensional datasets. However, currently an R implementation of APCA is only available for Spectra data in the ChemoSpec package, whereas ASCA is based on average calculations on the indices of up to three design matrices. Thus, no statistical inference on estimated effects is provided. Moreover, ASCA is not available in an R package.Here, we present an R implementation for ANOVA decomposition with PCA/PLS analysis that allows the user to specify (through a flexible formula interface), almost any linear model with the associated inference on the estimated effects, as well as to display functions to explore results both of PCA and PLS. We describe the model, its implementation and two high-throughput microarray examples: one applied to interaction pattern analysis and the other to quality assessment.

Date: 2014-01-25
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.jstatsoft.org/index.php/jss/article/view/v056i07/v56i07.pdf
https://www.jstatsoft.org/index.php/jss/article/do ... 7/lmdme_1.4.0.tar.gz
https://www.jstatsoft.org/index.php/jss/article/do ... ile/v056i07/v56i07.R
https://www.jstatsoft.org/index.php/jss/article/do ... 56i07/example2.RData

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:056:i07

DOI: 10.18637/jss.v056.i07

Access Statistics for this article

Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis

More articles in Journal of Statistical Software from Foundation for Open Access Statistics
Bibliographic data for series maintained by Christopher F. Baum ().