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trumpet: transcriptome-guided quality assessment of m(6)A-seq data
BACKGROUND: Methylated RNA immunoprecipitation sequencing (MeRIP-seq or m(6)A-seq) has been extensively used for profiling transcriptome-wide distribution of RNA N6-Methyl-Adnosine methylation. However, due to the intrinsic properties of RNA molecules and the intricate procedures of this technique,...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6044007/ https://www.ncbi.nlm.nih.gov/pubmed/30001693 http://dx.doi.org/10.1186/s12859-018-2266-3 |
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author | Zhang, Teng Zhang, Shao-Wu Zhang, Lin Meng, Jia |
author_facet | Zhang, Teng Zhang, Shao-Wu Zhang, Lin Meng, Jia |
author_sort | Zhang, Teng |
collection | PubMed |
description | BACKGROUND: Methylated RNA immunoprecipitation sequencing (MeRIP-seq or m(6)A-seq) has been extensively used for profiling transcriptome-wide distribution of RNA N6-Methyl-Adnosine methylation. However, due to the intrinsic properties of RNA molecules and the intricate procedures of this technique, m(6)A-seq data often suffer from various flaws. A convenient and comprehensive tool is needed to assess the quality of m(6)A-seq data to ensure that they are suitable for subsequent analysis. RESULTS: From a technical perspective, m(6)A-seq can be considered as a combination of ChIP-seq and RNA-seq; hence, by effectively combing the data quality assessment metrics of the two techniques, we developed the trumpet R package for evaluation of m(6)A-seq data quality. The trumpet package takes the aligned BAM files from m(6)A-seq data together with the transcriptome information as the inputs to generate a quality assessment report in the HTML format. CONCLUSIONS: The trumpet R package makes a valuable tool for assessing the data quality of m(6)A-seq, and it is also applicable to other fragmented RNA immunoprecipitation sequencing techniques, including m(1)A-seq, CeU-Seq, Ψ-seq, etc. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2266-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6044007 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-60440072018-07-13 trumpet: transcriptome-guided quality assessment of m(6)A-seq data Zhang, Teng Zhang, Shao-Wu Zhang, Lin Meng, Jia BMC Bioinformatics Software BACKGROUND: Methylated RNA immunoprecipitation sequencing (MeRIP-seq or m(6)A-seq) has been extensively used for profiling transcriptome-wide distribution of RNA N6-Methyl-Adnosine methylation. However, due to the intrinsic properties of RNA molecules and the intricate procedures of this technique, m(6)A-seq data often suffer from various flaws. A convenient and comprehensive tool is needed to assess the quality of m(6)A-seq data to ensure that they are suitable for subsequent analysis. RESULTS: From a technical perspective, m(6)A-seq can be considered as a combination of ChIP-seq and RNA-seq; hence, by effectively combing the data quality assessment metrics of the two techniques, we developed the trumpet R package for evaluation of m(6)A-seq data quality. The trumpet package takes the aligned BAM files from m(6)A-seq data together with the transcriptome information as the inputs to generate a quality assessment report in the HTML format. CONCLUSIONS: The trumpet R package makes a valuable tool for assessing the data quality of m(6)A-seq, and it is also applicable to other fragmented RNA immunoprecipitation sequencing techniques, including m(1)A-seq, CeU-Seq, Ψ-seq, etc. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2266-3) contains supplementary material, which is available to authorized users. BioMed Central 2018-07-13 /pmc/articles/PMC6044007/ /pubmed/30001693 http://dx.doi.org/10.1186/s12859-018-2266-3 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 | Software Zhang, Teng Zhang, Shao-Wu Zhang, Lin Meng, Jia trumpet: transcriptome-guided quality assessment of m(6)A-seq data |
title | trumpet: transcriptome-guided quality assessment of m(6)A-seq data |
title_full | trumpet: transcriptome-guided quality assessment of m(6)A-seq data |
title_fullStr | trumpet: transcriptome-guided quality assessment of m(6)A-seq data |
title_full_unstemmed | trumpet: transcriptome-guided quality assessment of m(6)A-seq data |
title_short | trumpet: transcriptome-guided quality assessment of m(6)A-seq data |
title_sort | trumpet: transcriptome-guided quality assessment of m(6)a-seq data |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6044007/ https://www.ncbi.nlm.nih.gov/pubmed/30001693 http://dx.doi.org/10.1186/s12859-018-2266-3 |
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