Cargando…

Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE)

Small sample sizes combined with high person-to-person variability can make it difficult to detect significant gene expression changes from transcriptional profiling studies. Subtle, but coordinated, gene expression changes may be detected using gene set analysis approaches. Meta-analysis is another...

Descripción completa

Detalles Bibliográficos
Autores principales: Meng, Hailong, Yaari, Gur, Bolen, Christopher R., Avey, Stefan, Kleinstein, Steven H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6461294/
https://www.ncbi.nlm.nih.gov/pubmed/30939133
http://dx.doi.org/10.1371/journal.pcbi.1006899
_version_ 1783410480592715776
author Meng, Hailong
Yaari, Gur
Bolen, Christopher R.
Avey, Stefan
Kleinstein, Steven H.
author_facet Meng, Hailong
Yaari, Gur
Bolen, Christopher R.
Avey, Stefan
Kleinstein, Steven H.
author_sort Meng, Hailong
collection PubMed
description Small sample sizes combined with high person-to-person variability can make it difficult to detect significant gene expression changes from transcriptional profiling studies. Subtle, but coordinated, gene expression changes may be detected using gene set analysis approaches. Meta-analysis is another approach to increase the power to detect biologically relevant changes by integrating information from multiple studies. Here, we present a framework that combines both approaches and allows for meta-analysis of gene sets. QuSAGE meta-analysis extends our previously published QuSAGE framework, which offers several advantages for gene set analysis, including fully accounting for gene-gene correlations and quantifying gene set activity as a full probability density function. Application of QuSAGE meta-analysis to influenza vaccination response shows it can detect significant activity that is not apparent in individual studies.
format Online
Article
Text
id pubmed-6461294
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-64612942019-05-03 Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE) Meng, Hailong Yaari, Gur Bolen, Christopher R. Avey, Stefan Kleinstein, Steven H. PLoS Comput Biol Research Article Small sample sizes combined with high person-to-person variability can make it difficult to detect significant gene expression changes from transcriptional profiling studies. Subtle, but coordinated, gene expression changes may be detected using gene set analysis approaches. Meta-analysis is another approach to increase the power to detect biologically relevant changes by integrating information from multiple studies. Here, we present a framework that combines both approaches and allows for meta-analysis of gene sets. QuSAGE meta-analysis extends our previously published QuSAGE framework, which offers several advantages for gene set analysis, including fully accounting for gene-gene correlations and quantifying gene set activity as a full probability density function. Application of QuSAGE meta-analysis to influenza vaccination response shows it can detect significant activity that is not apparent in individual studies. Public Library of Science 2019-04-02 /pmc/articles/PMC6461294/ /pubmed/30939133 http://dx.doi.org/10.1371/journal.pcbi.1006899 Text en © 2019 Meng et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Meng, Hailong
Yaari, Gur
Bolen, Christopher R.
Avey, Stefan
Kleinstein, Steven H.
Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE)
title Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE)
title_full Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE)
title_fullStr Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE)
title_full_unstemmed Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE)
title_short Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE)
title_sort gene set meta-analysis with quantitative set analysis for gene expression (qusage)
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6461294/
https://www.ncbi.nlm.nih.gov/pubmed/30939133
http://dx.doi.org/10.1371/journal.pcbi.1006899
work_keys_str_mv AT menghailong genesetmetaanalysiswithquantitativesetanalysisforgeneexpressionqusage
AT yaarigur genesetmetaanalysiswithquantitativesetanalysisforgeneexpressionqusage
AT bolenchristopherr genesetmetaanalysiswithquantitativesetanalysisforgeneexpressionqusage
AT aveystefan genesetmetaanalysiswithquantitativesetanalysisforgeneexpressionqusage
AT kleinsteinstevenh genesetmetaanalysiswithquantitativesetanalysisforgeneexpressionqusage