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MPRAnalyze: statistical framework for massively parallel reporter assays

Massively parallel reporter assays (MPRAs) can measure the regulatory function of thousands of DNA sequences in a single experiment. Despite growing popularity, MPRA studies are limited by a lack of a unified framework for analyzing the resulting data. Here we present MPRAnalyze: a statistical frame...

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Autores principales: Ashuach, Tal, Fischer, David S., Kreimer, Anat, Ahituv, Nadav, Theis, Fabian J., Yosef, Nir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6717970/
https://www.ncbi.nlm.nih.gov/pubmed/31477158
http://dx.doi.org/10.1186/s13059-019-1787-z
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author Ashuach, Tal
Fischer, David S.
Kreimer, Anat
Ahituv, Nadav
Theis, Fabian J.
Yosef, Nir
author_facet Ashuach, Tal
Fischer, David S.
Kreimer, Anat
Ahituv, Nadav
Theis, Fabian J.
Yosef, Nir
author_sort Ashuach, Tal
collection PubMed
description Massively parallel reporter assays (MPRAs) can measure the regulatory function of thousands of DNA sequences in a single experiment. Despite growing popularity, MPRA studies are limited by a lack of a unified framework for analyzing the resulting data. Here we present MPRAnalyze: a statistical framework for analyzing MPRA count data. Our model leverages the unique structure of MPRA data to quantify the function of regulatory sequences, compare sequences’ activity across different conditions, and provide necessary flexibility in an evolving field. We demonstrate the accuracy and applicability of MPRAnalyze on simulated and published data and compare it with existing methods. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-019-1787-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-67179702019-09-06 MPRAnalyze: statistical framework for massively parallel reporter assays Ashuach, Tal Fischer, David S. Kreimer, Anat Ahituv, Nadav Theis, Fabian J. Yosef, Nir Genome Biol Method Massively parallel reporter assays (MPRAs) can measure the regulatory function of thousands of DNA sequences in a single experiment. Despite growing popularity, MPRA studies are limited by a lack of a unified framework for analyzing the resulting data. Here we present MPRAnalyze: a statistical framework for analyzing MPRA count data. Our model leverages the unique structure of MPRA data to quantify the function of regulatory sequences, compare sequences’ activity across different conditions, and provide necessary flexibility in an evolving field. We demonstrate the accuracy and applicability of MPRAnalyze on simulated and published data and compare it with existing methods. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-019-1787-z) contains supplementary material, which is available to authorized users. BioMed Central 2019-09-02 /pmc/articles/PMC6717970/ /pubmed/31477158 http://dx.doi.org/10.1186/s13059-019-1787-z 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
Ashuach, Tal
Fischer, David S.
Kreimer, Anat
Ahituv, Nadav
Theis, Fabian J.
Yosef, Nir
MPRAnalyze: statistical framework for massively parallel reporter assays
title MPRAnalyze: statistical framework for massively parallel reporter assays
title_full MPRAnalyze: statistical framework for massively parallel reporter assays
title_fullStr MPRAnalyze: statistical framework for massively parallel reporter assays
title_full_unstemmed MPRAnalyze: statistical framework for massively parallel reporter assays
title_short MPRAnalyze: statistical framework for massively parallel reporter assays
title_sort mpranalyze: statistical framework for massively parallel reporter assays
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6717970/
https://www.ncbi.nlm.nih.gov/pubmed/31477158
http://dx.doi.org/10.1186/s13059-019-1787-z
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