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IAOseq: inferring abundance of overlapping genes using RNA-seq data

BACKGROUND: Overlapping transcription constitutes a common mechanism for regulating gene expression. A major limitation of the overlapping transcription assays is the lack of high throughput expression data. RESULTS: We developed a new tool (IAOseq) that is based on reads distributions along the tra...

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Detalles Bibliográficos
Autores principales: Sun, Hong, Yang, Shuang, Tun, Liangliang, Li, Yixue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4331702/
https://www.ncbi.nlm.nih.gov/pubmed/25707673
http://dx.doi.org/10.1186/1471-2105-16-S1-S3
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author Sun, Hong
Yang, Shuang
Tun, Liangliang
Li, Yixue
author_facet Sun, Hong
Yang, Shuang
Tun, Liangliang
Li, Yixue
author_sort Sun, Hong
collection PubMed
description BACKGROUND: Overlapping transcription constitutes a common mechanism for regulating gene expression. A major limitation of the overlapping transcription assays is the lack of high throughput expression data. RESULTS: We developed a new tool (IAOseq) that is based on reads distributions along the transcribed regions to identify the expression levels of overlapping genes from standard RNA-seq data. Compared with five commonly used quantification methods, IAOseq showed better performance in the estimation accuracy of overlapping transcription levels. For the same strand overlapping transcription, currently existing high-throughput methods are rarely available to distinguish which strand was present in the original mRNA template. The IAOseq results showed that the commonly used methods gave an average of 1.6 fold overestimation of the expression levels of same strand overlapping genes. CONCLUSIONS: This work provides a useful tool for mining overlapping transcription levels from standard RNA-seq libraries. IAOseq could be used to help us understand the complex regulatory mechanism mediated by overlapping transcripts. IAOseq is freely available at http://lifecenter.sgst.cn/main/en/IAO_seq.jsp.
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spelling pubmed-43317022015-03-19 IAOseq: inferring abundance of overlapping genes using RNA-seq data Sun, Hong Yang, Shuang Tun, Liangliang Li, Yixue BMC Bioinformatics Proceedings BACKGROUND: Overlapping transcription constitutes a common mechanism for regulating gene expression. A major limitation of the overlapping transcription assays is the lack of high throughput expression data. RESULTS: We developed a new tool (IAOseq) that is based on reads distributions along the transcribed regions to identify the expression levels of overlapping genes from standard RNA-seq data. Compared with five commonly used quantification methods, IAOseq showed better performance in the estimation accuracy of overlapping transcription levels. For the same strand overlapping transcription, currently existing high-throughput methods are rarely available to distinguish which strand was present in the original mRNA template. The IAOseq results showed that the commonly used methods gave an average of 1.6 fold overestimation of the expression levels of same strand overlapping genes. CONCLUSIONS: This work provides a useful tool for mining overlapping transcription levels from standard RNA-seq libraries. IAOseq could be used to help us understand the complex regulatory mechanism mediated by overlapping transcripts. IAOseq is freely available at http://lifecenter.sgst.cn/main/en/IAO_seq.jsp. BioMed Central 2015-01-21 /pmc/articles/PMC4331702/ /pubmed/25707673 http://dx.doi.org/10.1186/1471-2105-16-S1-S3 Text en Copyright © 2015 Sun et al.; licensee BioMed Central Ltd. 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 work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Proceedings
Sun, Hong
Yang, Shuang
Tun, Liangliang
Li, Yixue
IAOseq: inferring abundance of overlapping genes using RNA-seq data
title IAOseq: inferring abundance of overlapping genes using RNA-seq data
title_full IAOseq: inferring abundance of overlapping genes using RNA-seq data
title_fullStr IAOseq: inferring abundance of overlapping genes using RNA-seq data
title_full_unstemmed IAOseq: inferring abundance of overlapping genes using RNA-seq data
title_short IAOseq: inferring abundance of overlapping genes using RNA-seq data
title_sort iaoseq: inferring abundance of overlapping genes using rna-seq data
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4331702/
https://www.ncbi.nlm.nih.gov/pubmed/25707673
http://dx.doi.org/10.1186/1471-2105-16-S1-S3
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