Principal-oscillation-pattern analysis of gene expression.

Principal-oscillation-pattern analysis of gene expression.

Principal-oscillation-pattern (POP) analysis is a multivariate and systematic technique for identifying the dynamic characteristics of a system from time-series data. In this study, we demonstrate the first application of POP analysis to genome-wide time-series gene-expression data. We use POP analy...

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Autores principales: Daifeng Wang, Ari Arapostathis, Claus O Wilke, Mia K Markey
Formato: article
Lenguaje:EN
Publicado: Public Library of Science (PLoS) 2012
Materias:
Medicine
R
Science
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Acceso en línea:https://doaj.org/article/4ca790c64bbd4b15a62ee76f3a618481
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spelling oai:doaj.org-article:4ca790c64bbd4b15a62ee76f3a6184812021-11-18T07:30:40ZPrincipal-oscillation-pattern analysis of gene expression.1932-620310.1371/journal.pone.0028805https://doaj.org/article/4ca790c64bbd4b15a62ee76f3a6184812012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22253697/?tool=EBIhttps://doaj.org/toc/1932-6203Principal-oscillation-pattern (POP) analysis is a multivariate and systematic technique for identifying the dynamic characteristics of a system from time-series data. In this study, we demonstrate the first application of POP analysis to genome-wide time-series gene-expression data. We use POP analysis to infer oscillation patterns in gene expression. Typically, a genomic system matrix cannot be directly estimated because the number of genes is usually much larger than the number of time points in a genomic study. Thus, we first identify the POPs of the eigen-genomic system that consists of the first few significant eigengenes obtained by singular value decomposition. By using the linear relationship between eigengenes and genes, we then infer the POPs of the genes. Both simulation data and real-world data are used in this study to demonstrate the applicability of POP analysis to genomic data. We show that POP analysis not only compares favorably with experiments and existing computational methods, but that it also provides complementary information relative to other approaches.Daifeng WangAri ArapostathisClaus O WilkeMia K MarkeyPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 1, p e28805 (2012)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Daifeng Wang
Ari Arapostathis
Claus O Wilke
Mia K Markey
Principal-oscillation-pattern analysis of gene expression.
description Principal-oscillation-pattern (POP) analysis is a multivariate and systematic technique for identifying the dynamic characteristics of a system from time-series data. In this study, we demonstrate the first application of POP analysis to genome-wide time-series gene-expression data. We use POP analysis to infer oscillation patterns in gene expression. Typically, a genomic system matrix cannot be directly estimated because the number of genes is usually much larger than the number of time points in a genomic study. Thus, we first identify the POPs of the eigen-genomic system that consists of the first few significant eigengenes obtained by singular value decomposition. By using the linear relationship between eigengenes and genes, we then infer the POPs of the genes. Both simulation data and real-world data are used in this study to demonstrate the applicability of POP analysis to genomic data. We show that POP analysis not only compares favorably with experiments and existing computational methods, but that it also provides complementary information relative to other approaches.
format article
author Daifeng Wang
Ari Arapostathis
Claus O Wilke
Mia K Markey
author_facet Daifeng Wang
Ari Arapostathis
Claus O Wilke
Mia K Markey
author_sort Daifeng Wang
title Principal-oscillation-pattern analysis of gene expression.
title_short Principal-oscillation-pattern analysis of gene expression.
title_full Principal-oscillation-pattern analysis of gene expression.
title_fullStr Principal-oscillation-pattern analysis of gene expression.
title_full_unstemmed Principal-oscillation-pattern analysis of gene expression.
title_sort principal-oscillation-pattern analysis of gene expression.
publisher Public Library of Science (PLoS)
publishDate 2012
url https://doaj.org/article/4ca790c64bbd4b15a62ee76f3a618481
work_keys_str_mv AT daifengwang principaloscillationpatternanalysisofgeneexpression
AT ariarapostathis principaloscillationpatternanalysisofgeneexpression
AT clausowilke principaloscillationpatternanalysisofgeneexpression
AT miakmarkey principaloscillationpatternanalysisofgeneexpression
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