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Soft truncation thresholding for gene set analysis of RNA-seq data: Application to a vaccine study

Gene set analysis (GSA) has been used for analysis of microarray data to aid the interpretation and to increase statistical power. With the advent of next-generation sequencing, the use of GSA is even more relevant, as studies are often conducted on a small number of samples. We propose the use of s...

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Autores principales: Fridley, Brooke L., Jenkins, Gregory D., Grill, Diane E., Kennedy, Richard B., Poland, Gregory A., Oberg, Ann L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3793215/
https://www.ncbi.nlm.nih.gov/pubmed/24104466
http://dx.doi.org/10.1038/srep02898
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author Fridley, Brooke L.
Jenkins, Gregory D.
Grill, Diane E.
Kennedy, Richard B.
Poland, Gregory A.
Oberg, Ann L.
author_facet Fridley, Brooke L.
Jenkins, Gregory D.
Grill, Diane E.
Kennedy, Richard B.
Poland, Gregory A.
Oberg, Ann L.
author_sort Fridley, Brooke L.
collection PubMed
description Gene set analysis (GSA) has been used for analysis of microarray data to aid the interpretation and to increase statistical power. With the advent of next-generation sequencing, the use of GSA is even more relevant, as studies are often conducted on a small number of samples. We propose the use of soft truncation thresholding and the Gamma Method (GM) to determine significant gene set (GS), where a generalized linear model is used to assess per-gene significance. The approach was compared to other methods using an extensive simulation study and RNA-seq data from smallpox vaccine study. The GM was found to outperform other proposed methods. Application of the GM to the smallpox vaccine study found the GSs to be moderately associated with response, including focal adhesion (p = 0.04) and extracellular matrix receptor interaction (p = 0.05). The application of GSA to RNA-seq data will provide new insights into the genomic basis of complex traits.
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spelling pubmed-37932152013-10-18 Soft truncation thresholding for gene set analysis of RNA-seq data: Application to a vaccine study Fridley, Brooke L. Jenkins, Gregory D. Grill, Diane E. Kennedy, Richard B. Poland, Gregory A. Oberg, Ann L. Sci Rep Article Gene set analysis (GSA) has been used for analysis of microarray data to aid the interpretation and to increase statistical power. With the advent of next-generation sequencing, the use of GSA is even more relevant, as studies are often conducted on a small number of samples. We propose the use of soft truncation thresholding and the Gamma Method (GM) to determine significant gene set (GS), where a generalized linear model is used to assess per-gene significance. The approach was compared to other methods using an extensive simulation study and RNA-seq data from smallpox vaccine study. The GM was found to outperform other proposed methods. Application of the GM to the smallpox vaccine study found the GSs to be moderately associated with response, including focal adhesion (p = 0.04) and extracellular matrix receptor interaction (p = 0.05). The application of GSA to RNA-seq data will provide new insights into the genomic basis of complex traits. Nature Publishing Group 2013-10-09 /pmc/articles/PMC3793215/ /pubmed/24104466 http://dx.doi.org/10.1038/srep02898 Text en Copyright © 2013, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by/3.0/ This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/
spellingShingle Article
Fridley, Brooke L.
Jenkins, Gregory D.
Grill, Diane E.
Kennedy, Richard B.
Poland, Gregory A.
Oberg, Ann L.
Soft truncation thresholding for gene set analysis of RNA-seq data: Application to a vaccine study
title Soft truncation thresholding for gene set analysis of RNA-seq data: Application to a vaccine study
title_full Soft truncation thresholding for gene set analysis of RNA-seq data: Application to a vaccine study
title_fullStr Soft truncation thresholding for gene set analysis of RNA-seq data: Application to a vaccine study
title_full_unstemmed Soft truncation thresholding for gene set analysis of RNA-seq data: Application to a vaccine study
title_short Soft truncation thresholding for gene set analysis of RNA-seq data: Application to a vaccine study
title_sort soft truncation thresholding for gene set analysis of rna-seq data: application to a vaccine study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3793215/
https://www.ncbi.nlm.nih.gov/pubmed/24104466
http://dx.doi.org/10.1038/srep02898
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