A novel dynamic impact approach (DIA) for functional analysis of time-course omics studies: validation using the bovine mammary transcriptome.

The overrepresented approach (ORA) is the most widely-accepted method for functional analysis of microarray datasets. The ORA is computationally-efficient and robust; however, it suffers from the inability of comparing results from multiple gene lists particularly with time-course experiments or tho...

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Autores principales:	Massimo Bionaz, Kathiravan Periasamy, Sandra L Rodriguez-Zas, Walter L Hurley, Juan J Loor
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/588d7501e95e4b059eec58b866cf24f6
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spelling	oai:doaj.org-article:588d7501e95e4b059eec58b866cf24f62021-11-18T07:25:02ZA novel dynamic impact approach (DIA) for functional analysis of time-course omics studies: validation using the bovine mammary transcriptome.1932-620310.1371/journal.pone.0032455https://doaj.org/article/588d7501e95e4b059eec58b866cf24f62012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22438877/?tool=EBIhttps://doaj.org/toc/1932-6203The overrepresented approach (ORA) is the most widely-accepted method for functional analysis of microarray datasets. The ORA is computationally-efficient and robust; however, it suffers from the inability of comparing results from multiple gene lists particularly with time-course experiments or those involving multiple treatments. To overcome such limitation a novel method termed Dynamic Impact Approach (DIA) is proposed. The DIA provides an estimate of the biological impact of the experimental conditions and the direction of the impact. The impact is obtained by combining the proportion of differentially expressed genes (DEG) with the log2 mean fold change and mean -log P-value of genes associated with the biological term. The direction of the impact is calculated as the difference of the impact of up-regulated DEG and down-regulated DEG associated with the biological term. The DIA was validated using microarray data from a time-course experiment of bovine mammary gland across the lactation cycle. Several annotation databases were analyzed with DIA and compared to the same analysis performed by the ORA. The DIA highlighted that during lactation both BTA6 and BTA14 were the most impacted chromosomes; among Uniprot tissues those related with lactating mammary gland were the most positively-impacted; within KEGG pathways 'Galactose metabolism' and several metabolism categories related to lipid synthesis were among the most impacted and induced; within Gene Ontology "lactose biosynthesis" among Biological processes and "Lactose synthase activity" and "Stearoyl-CoA 9-desaturase activity" among Molecular processes were the most impacted and induced. With the exception of the terms 'Milk', 'Milk protein' and 'Mammary gland' among Uniprot tissues and SP_PIR_Keyword, the use of ORA failed to capture as significantly-enriched (i.e., biologically relevant) any term known to be associated with lactating mammary gland. Results indicate the DIA is a biologically-sound approach for analysis of time-course experiments. This tool represents an alternative to ORA for functional analysis.Massimo BionazKathiravan PeriasamySandra L Rodriguez-ZasWalter L HurleyJuan J LoorPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 3, p e32455 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Massimo Bionaz Kathiravan Periasamy Sandra L Rodriguez-Zas Walter L Hurley Juan J Loor A novel dynamic impact approach (DIA) for functional analysis of time-course omics studies: validation using the bovine mammary transcriptome.
description	The overrepresented approach (ORA) is the most widely-accepted method for functional analysis of microarray datasets. The ORA is computationally-efficient and robust; however, it suffers from the inability of comparing results from multiple gene lists particularly with time-course experiments or those involving multiple treatments. To overcome such limitation a novel method termed Dynamic Impact Approach (DIA) is proposed. The DIA provides an estimate of the biological impact of the experimental conditions and the direction of the impact. The impact is obtained by combining the proportion of differentially expressed genes (DEG) with the log2 mean fold change and mean -log P-value of genes associated with the biological term. The direction of the impact is calculated as the difference of the impact of up-regulated DEG and down-regulated DEG associated with the biological term. The DIA was validated using microarray data from a time-course experiment of bovine mammary gland across the lactation cycle. Several annotation databases were analyzed with DIA and compared to the same analysis performed by the ORA. The DIA highlighted that during lactation both BTA6 and BTA14 were the most impacted chromosomes; among Uniprot tissues those related with lactating mammary gland were the most positively-impacted; within KEGG pathways 'Galactose metabolism' and several metabolism categories related to lipid synthesis were among the most impacted and induced; within Gene Ontology "lactose biosynthesis" among Biological processes and "Lactose synthase activity" and "Stearoyl-CoA 9-desaturase activity" among Molecular processes were the most impacted and induced. With the exception of the terms 'Milk', 'Milk protein' and 'Mammary gland' among Uniprot tissues and SP_PIR_Keyword, the use of ORA failed to capture as significantly-enriched (i.e., biologically relevant) any term known to be associated with lactating mammary gland. Results indicate the DIA is a biologically-sound approach for analysis of time-course experiments. This tool represents an alternative to ORA for functional analysis.
format	article
author	Massimo Bionaz Kathiravan Periasamy Sandra L Rodriguez-Zas Walter L Hurley Juan J Loor
author_facet	Massimo Bionaz Kathiravan Periasamy Sandra L Rodriguez-Zas Walter L Hurley Juan J Loor
author_sort	Massimo Bionaz
title	A novel dynamic impact approach (DIA) for functional analysis of time-course omics studies: validation using the bovine mammary transcriptome.
title_short	A novel dynamic impact approach (DIA) for functional analysis of time-course omics studies: validation using the bovine mammary transcriptome.
title_full	A novel dynamic impact approach (DIA) for functional analysis of time-course omics studies: validation using the bovine mammary transcriptome.
title_fullStr	A novel dynamic impact approach (DIA) for functional analysis of time-course omics studies: validation using the bovine mammary transcriptome.
title_full_unstemmed	A novel dynamic impact approach (DIA) for functional analysis of time-course omics studies: validation using the bovine mammary transcriptome.
title_sort	novel dynamic impact approach (dia) for functional analysis of time-course omics studies: validation using the bovine mammary transcriptome.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/588d7501e95e4b059eec58b866cf24f6
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A novel dynamic impact approach (DIA) for functional analysis of time-course omics studies: validation using the bovine mammary transcriptome.

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