Statistical Methods for Comparative Phenomics Using High-Throughput Phenotype Microarrays

Sturino Joseph, Zorych Ivan, Mallick Bani, Pokusaeva Karina, Chang Ying-Ying, Carroll Raymond J and Bliznuyk Nikolay
Additional contact information
Sturino Joseph: Texas A&M University
Zorych Ivan: Texas A&M University
Mallick Bani: Texas A&M University
Pokusaeva Karina: Texas A&M University
Chang Ying-Ying: Texas A&M University
Carroll Raymond J: Texas A&M University
Bliznuyk Nikolay: Texas A&M University

The International Journal of Biostatistics, 2010, vol. 6, issue 1, 21

Abstract: We propose statistical methods for comparing phenomics data generated by the Biolog Phenotype Microarray (PM) platform for high-throughput phenotyping. Instead of the routinely used visual inspection of data with no sound inferential basis, we develop two approaches. The first approach is based on quantifying the distance between mean or median curves from two treatments and then applying a permutation test; we also consider a permutation test applied to areas under mean curves. The second approach employs functional principal component analysis. Properties of the proposed methods are investigated on both simulated data and data sets from the PM platform.

Keywords: functional data analysis; principal components; permutation tests; phenotype microarrays; high-throughput phenotyping; phenomics; Biolog (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://doi.org/10.2202/1557-4679.1227 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

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:bpj:ijbist:v:6:y:2010:i:1:n:29

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/ijb/html

DOI: 10.2202/1557-4679.1227

Access Statistics for this article

The International Journal of Biostatistics is currently edited by Antoine Chambaz, Alan E. Hubbard and Mark J. van der Laan

More articles in The International Journal of Biostatistics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().