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Identification of Differentially Expressed Genes in RNA-seq Data of Arabidopsis thaliana: A Compound Distribution Approach
Gene expression is the process by which information from a gene is used in the synthesis of a functional gene product, which may be proteins. A gene is declared differentially expressed if an observed difference or change in read counts or expression levels between two experimental conditions is sta...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Mary Ann Liebert, Inc.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4827276/ https://www.ncbi.nlm.nih.gov/pubmed/26949988 http://dx.doi.org/10.1089/cmb.2015.0205 |
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author | Anjum, Arfa Jaggi, Seema Varghese, Eldho Lall, Shwetank Bhowmik, Arpan Rai, Anil |
author_facet | Anjum, Arfa Jaggi, Seema Varghese, Eldho Lall, Shwetank Bhowmik, Arpan Rai, Anil |
author_sort | Anjum, Arfa |
collection | PubMed |
description | Gene expression is the process by which information from a gene is used in the synthesis of a functional gene product, which may be proteins. A gene is declared differentially expressed if an observed difference or change in read counts or expression levels between two experimental conditions is statistically significant. To identify differentially expressed genes between two conditions, it is important to find statistical distributional property of the data to approximate the nature of differential genes. In the present study, the focus is mainly to investigate the differential gene expression analysis for sequence data based on compound distribution model. This approach was applied in RNA-seq count data of Arabidopsis thaliana and it has been found that compound Poisson distribution is more appropriate to capture the variability as compared with Poisson distribution. Thus, fitting of appropriate distribution to gene expression data provides statistically sound cutoff values for identifying differentially expressed genes. |
format | Online Article Text |
id | pubmed-4827276 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Mary Ann Liebert, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-48272762016-04-20 Identification of Differentially Expressed Genes in RNA-seq Data of Arabidopsis thaliana: A Compound Distribution Approach Anjum, Arfa Jaggi, Seema Varghese, Eldho Lall, Shwetank Bhowmik, Arpan Rai, Anil J Comput Biol Research Articles Gene expression is the process by which information from a gene is used in the synthesis of a functional gene product, which may be proteins. A gene is declared differentially expressed if an observed difference or change in read counts or expression levels between two experimental conditions is statistically significant. To identify differentially expressed genes between two conditions, it is important to find statistical distributional property of the data to approximate the nature of differential genes. In the present study, the focus is mainly to investigate the differential gene expression analysis for sequence data based on compound distribution model. This approach was applied in RNA-seq count data of Arabidopsis thaliana and it has been found that compound Poisson distribution is more appropriate to capture the variability as compared with Poisson distribution. Thus, fitting of appropriate distribution to gene expression data provides statistically sound cutoff values for identifying differentially expressed genes. Mary Ann Liebert, Inc. 2016-04-01 /pmc/articles/PMC4827276/ /pubmed/26949988 http://dx.doi.org/10.1089/cmb.2015.0205 Text en © Arfa Anjum et al., 2016. Published by Mary Ann Liebert, Inc. This Open Access article is distributed under the terms of the Creative Commons Attribution Noncommercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits any noncommercial use, distribution, and reproduction in any medium, provided the orginal author(s) and the source are credited. |
spellingShingle | Research Articles Anjum, Arfa Jaggi, Seema Varghese, Eldho Lall, Shwetank Bhowmik, Arpan Rai, Anil Identification of Differentially Expressed Genes in RNA-seq Data of Arabidopsis thaliana: A Compound Distribution Approach |
title | Identification of Differentially Expressed Genes in RNA-seq Data of Arabidopsis thaliana: A Compound Distribution Approach |
title_full | Identification of Differentially Expressed Genes in RNA-seq Data of Arabidopsis thaliana: A Compound Distribution Approach |
title_fullStr | Identification of Differentially Expressed Genes in RNA-seq Data of Arabidopsis thaliana: A Compound Distribution Approach |
title_full_unstemmed | Identification of Differentially Expressed Genes in RNA-seq Data of Arabidopsis thaliana: A Compound Distribution Approach |
title_short | Identification of Differentially Expressed Genes in RNA-seq Data of Arabidopsis thaliana: A Compound Distribution Approach |
title_sort | identification of differentially expressed genes in rna-seq data of arabidopsis thaliana: a compound distribution approach |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4827276/ https://www.ncbi.nlm.nih.gov/pubmed/26949988 http://dx.doi.org/10.1089/cmb.2015.0205 |
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