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Comparing Bioinformatic Gene Expression Profiling Methods: Microarray and RNA-Seq

Understanding the control of gene expression is critical for our understanding of the relationship between genotype and phenotype. The need for reliable assessment of transcript abundance in biological samples has driven scientists to develop novel technologies such as DNA microarray and RNA-Seq to...

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Autores principales: Mantione, Kirk J, Kream, Richard M., Kuzelova, Hana, Ptacek, Radek, Raboch, Jiri, Samuel, Joshua M., Stefano, George B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scientific Literature, Inc. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4152252/
https://www.ncbi.nlm.nih.gov/pubmed/25149683
http://dx.doi.org/10.12659/MSMBR.892101
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author Mantione, Kirk J
Kream, Richard M.
Kuzelova, Hana
Ptacek, Radek
Raboch, Jiri
Samuel, Joshua M.
Stefano, George B.
author_facet Mantione, Kirk J
Kream, Richard M.
Kuzelova, Hana
Ptacek, Radek
Raboch, Jiri
Samuel, Joshua M.
Stefano, George B.
author_sort Mantione, Kirk J
collection PubMed
description Understanding the control of gene expression is critical for our understanding of the relationship between genotype and phenotype. The need for reliable assessment of transcript abundance in biological samples has driven scientists to develop novel technologies such as DNA microarray and RNA-Seq to meet this demand. This review focuses on comparing the two most useful methods for whole transcriptome gene expression profiling. Microarrays are reliable and more cost effective than RNA-Seq for gene expression profiling in model organisms. RNA-Seq will eventually be used more routinely than microarray, but right now the techniques can be complementary to each other. Microarrays will not become obsolete but might be relegated to only a few uses. RNA-Seq clearly has a bright future in bioinformatic data collection.
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spelling pubmed-41522522014-09-04 Comparing Bioinformatic Gene Expression Profiling Methods: Microarray and RNA-Seq Mantione, Kirk J Kream, Richard M. Kuzelova, Hana Ptacek, Radek Raboch, Jiri Samuel, Joshua M. Stefano, George B. Med Sci Monit Basic Res Molecular Biology Understanding the control of gene expression is critical for our understanding of the relationship between genotype and phenotype. The need for reliable assessment of transcript abundance in biological samples has driven scientists to develop novel technologies such as DNA microarray and RNA-Seq to meet this demand. This review focuses on comparing the two most useful methods for whole transcriptome gene expression profiling. Microarrays are reliable and more cost effective than RNA-Seq for gene expression profiling in model organisms. RNA-Seq will eventually be used more routinely than microarray, but right now the techniques can be complementary to each other. Microarrays will not become obsolete but might be relegated to only a few uses. RNA-Seq clearly has a bright future in bioinformatic data collection. International Scientific Literature, Inc. 2014-08-23 /pmc/articles/PMC4152252/ /pubmed/25149683 http://dx.doi.org/10.12659/MSMBR.892101 Text en © Med Sci Monit, 2014 This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License
spellingShingle Molecular Biology
Mantione, Kirk J
Kream, Richard M.
Kuzelova, Hana
Ptacek, Radek
Raboch, Jiri
Samuel, Joshua M.
Stefano, George B.
Comparing Bioinformatic Gene Expression Profiling Methods: Microarray and RNA-Seq
title Comparing Bioinformatic Gene Expression Profiling Methods: Microarray and RNA-Seq
title_full Comparing Bioinformatic Gene Expression Profiling Methods: Microarray and RNA-Seq
title_fullStr Comparing Bioinformatic Gene Expression Profiling Methods: Microarray and RNA-Seq
title_full_unstemmed Comparing Bioinformatic Gene Expression Profiling Methods: Microarray and RNA-Seq
title_short Comparing Bioinformatic Gene Expression Profiling Methods: Microarray and RNA-Seq
title_sort comparing bioinformatic gene expression profiling methods: microarray and rna-seq
topic Molecular Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4152252/
https://www.ncbi.nlm.nih.gov/pubmed/25149683
http://dx.doi.org/10.12659/MSMBR.892101
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