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MPRAnalyze: statistical framework for massively parallel reporter assays.
Ashuach, Tal; Fischer, David S; Kreimer, Anat; Ahituv, Nadav; Theis, Fabian J; Yosef, Nir.
Afiliação
  • Ashuach T; Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California, USA.
  • Fischer DS; Center for Computational Biology, University of California Berkeley, Berkeley, California, USA.
  • Kreimer A; Institute of Computational Biology, Helmholz Zentrum München, Neuherberg, Germany.
  • Ahituv N; TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany.
  • Theis FJ; Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California, USA.
  • Yosef N; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California, USA.
Genome Biol ; 20(1): 183, 2019 09 02.
Article em En | MEDLINE | ID: mdl-31477158
ABSTRACT
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bioensaio / Software / Estatística como Assunto / Genes Reporter / Sequenciamento de Nucleotídeos em Larga Escala Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bioensaio / Software / Estatística como Assunto / Genes Reporter / Sequenciamento de Nucleotídeos em Larga Escala Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article