Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/21416
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | PADAYACHEE, Trishanta | - |
dc.contributor.author | KHAMIAKOVA, Tatsiana | - |
dc.contributor.author | SHKEDY, Ziv | - |
dc.contributor.author | Perola, Markus | - |
dc.contributor.author | Salo, Perttu | - |
dc.contributor.author | BURZYKOWSKI, Tomasz | - |
dc.date.accessioned | 2016-06-03T09:42:34Z | - |
dc.date.available | 2016-06-03T09:42:34Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | PLoS One, 11 (2) | - |
dc.identifier.issn | 1932-6203 | - |
dc.identifier.uri | http://hdl.handle.net/1942/21416 | - |
dc.description.abstract | Investigating whether metabolites regulate the co-expression of a predefined gene module is one of the relevant questions posed in the integrative analysis of metabolomic and transcriptomic data. This article concerns the integrative analysis of the two high-dimensional datasets by means of multivariate models and statistical tests for the dependence between metabolites and the co-expression of a gene module. The general linear model (GLM) for correlated data that we propose models the dependence between adjusted gene expression values through a block-diagonal variance-covariance structure formed by metabolicsubset specific general variance-covariance blocks. Performance of statistical tests for the inference of conditional co-expression are evaluated through a simulation study. The proposed methodology is applied to the gene expression data of the previously characterized lipid-leukocyte module. Our results show that the GLM approach improves on a previous approach by being less prone to the detection of spurious conditional co-expression. | - |
dc.description.sponsorship | This research was funded by the MIMOmics grant of the European Union's Seventh Framework Programme (FP7-Health-F5-2012) under the grant agreement number 305280. The support of the IAP Research Network of the Belgian state (Belgian Science Policy) P7/06 is gratefully acknowledged. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. | - |
dc.language.iso | en | - |
dc.rights | Copyright: © 2016 Padayachee et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | - |
dc.title | The Detection of Metabolite-Mediated Gene Module Co-Expression Using Multivariate Linear Models | - |
dc.type | Journal Contribution | - |
dc.identifier.issue | 2 | - |
dc.identifier.volume | 11 | - |
local.format.pages | 17 | - |
local.bibliographicCitation.jcat | A1 | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.identifier.doi | 10.1371/journal.pone.0150257 | - |
dc.identifier.isi | 000371274400111 | - |
item.contributor | PADAYACHEE, Trishanta | - |
item.contributor | KHAMIAKOVA, Tatsiana | - |
item.contributor | SHKEDY, Ziv | - |
item.contributor | Perola, Markus | - |
item.contributor | Salo, Perttu | - |
item.contributor | BURZYKOWSKI, Tomasz | - |
item.fulltext | With Fulltext | - |
item.validation | ecoom 2017 | - |
item.fullcitation | PADAYACHEE, Trishanta; KHAMIAKOVA, Tatsiana; SHKEDY, Ziv; Perola, Markus; Salo, Perttu & BURZYKOWSKI, Tomasz (2016) The Detection of Metabolite-Mediated Gene Module Co-Expression Using Multivariate Linear Models. In: PLoS One, 11 (2). | - |
item.accessRights | Open Access | - |
crisitem.journal.issn | 1932-6203 | - |
crisitem.journal.eissn | 1932-6203 | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
journal.pone.0150257.PDF | Published version | 3.75 MB | Adobe PDF | View/Open |
SCOPUSTM
Citations
3
checked on Sep 2, 2020
WEB OF SCIENCETM
Citations
3
checked on Apr 30, 2024
Page view(s)
66
checked on Sep 6, 2022
Download(s)
102
checked on Sep 6, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.