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dStruct: identifying differentially reactive regions from RNA structurome profiling data

RNA biology is revolutionized by recent developments of diverse high-throughput technologies for transcriptome-wide profiling of molecular RNA structures. RNA structurome profiling data can be used to identify differentially structured regions between groups of samples. Existing methods are limited...

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Detalles Bibliográficos
Autores principales: Choudhary, Krishna, Lai, Yu-Hsuan, Tran, Elizabeth J., Aviran, Sharon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6385470/
https://www.ncbi.nlm.nih.gov/pubmed/30791935
http://dx.doi.org/10.1186/s13059-019-1641-3
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author Choudhary, Krishna
Lai, Yu-Hsuan
Tran, Elizabeth J.
Aviran, Sharon
author_facet Choudhary, Krishna
Lai, Yu-Hsuan
Tran, Elizabeth J.
Aviran, Sharon
author_sort Choudhary, Krishna
collection PubMed
description RNA biology is revolutionized by recent developments of diverse high-throughput technologies for transcriptome-wide profiling of molecular RNA structures. RNA structurome profiling data can be used to identify differentially structured regions between groups of samples. Existing methods are limited in scope to specific technologies and/or do not account for biological variation. Here, we present dStruct which is the first broadly applicable method for differential analysis accounting for biological variation in structurome profiling data. dStruct is compatible with diverse profiling technologies, is validated with experimental data and simulations, and outperforms existing methods. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-019-1641-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-63854702019-03-04 dStruct: identifying differentially reactive regions from RNA structurome profiling data Choudhary, Krishna Lai, Yu-Hsuan Tran, Elizabeth J. Aviran, Sharon Genome Biol Method RNA biology is revolutionized by recent developments of diverse high-throughput technologies for transcriptome-wide profiling of molecular RNA structures. RNA structurome profiling data can be used to identify differentially structured regions between groups of samples. Existing methods are limited in scope to specific technologies and/or do not account for biological variation. Here, we present dStruct which is the first broadly applicable method for differential analysis accounting for biological variation in structurome profiling data. dStruct is compatible with diverse profiling technologies, is validated with experimental data and simulations, and outperforms existing methods. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-019-1641-3) contains supplementary material, which is available to authorized users. BioMed Central 2019-02-21 /pmc/articles/PMC6385470/ /pubmed/30791935 http://dx.doi.org/10.1186/s13059-019-1641-3 Text en © The Author(s) 2019 Open Access This 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 Method
Choudhary, Krishna
Lai, Yu-Hsuan
Tran, Elizabeth J.
Aviran, Sharon
dStruct: identifying differentially reactive regions from RNA structurome profiling data
title dStruct: identifying differentially reactive regions from RNA structurome profiling data
title_full dStruct: identifying differentially reactive regions from RNA structurome profiling data
title_fullStr dStruct: identifying differentially reactive regions from RNA structurome profiling data
title_full_unstemmed dStruct: identifying differentially reactive regions from RNA structurome profiling data
title_short dStruct: identifying differentially reactive regions from RNA structurome profiling data
title_sort dstruct: identifying differentially reactive regions from rna structurome profiling data
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6385470/
https://www.ncbi.nlm.nih.gov/pubmed/30791935
http://dx.doi.org/10.1186/s13059-019-1641-3
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