@article{Herrmann2019-10-16PolyA-50959,
  year={2019},
  doi={10.1093/nar/gkz918},
  title={PolyASite 2.0 : a consolidated atlas of polyadenylation sites from 3′ end sequencing},
  number={D1},
  volume={48},
  issn={0301-5610},
  journal={Nucleic Acids Research},
  pages={D174--D179},
  author={Herrmann, Christina J. and Schmidt, Ralf and Kanitz, Alexander and Artimo, Panu and Gruber, Andreas J. and Zavolan, Mihaela}
}

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    <dc:contributor>Gruber, Andreas J.</dc:contributor>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2020-09-22T10:07:38Z</dc:date>
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    <dcterms:title>PolyASite 2.0 : a consolidated atlas of polyadenylation sites from 3′ end sequencing</dcterms:title>
    <dc:language>eng</dc:language>
    <dcterms:issued>2019-10-16</dcterms:issued>
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    <dcterms:abstract xml:lang="eng">Generated by 3′ end cleavage and polyadenylation at alternative polyadenylation (poly(A)) sites, alternative terminal exons account for much of the variation between human transcript isoforms. More than a dozen protocols have been developed so far for capturing and sequencing RNA 3′ ends from a variety of cell types and species. In previous studies, we have used these data to uncover novel regulatory signals and cell type-specific isoforms. Here we present an update of the PolyASite (https://polyasite.unibas.ch) resource of poly(A) sites, constructed from publicly available human, mouse and worm 3′ end sequencing datasets by enforcing uniform quality measures, including the flagging of putative internal priming sites. Through integrated processing of all data, we identified and clustered sites that are closely spaced and share polyadenylation signals, as these are likely the result of stochastic variations in processing. For each cluster, we identified the representative - most frequently processed - site and estimated the relative use in the transcriptome across all samples. We have established a modern web portal for efficient finding, exploration and export of data. Database generation is fully automated, greatly facilitating incorporation of new datasets and the updating of underlying genome resources.</dcterms:abstract>
    <dc:creator>Gruber, Andreas J.</dc:creator>
    <dc:creator>Kanitz, Alexander</dc:creator>
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    <dc:creator>Herrmann, Christina J.</dc:creator>
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    <dc:creator>Zavolan, Mihaela</dc:creator>
    <dc:contributor>Herrmann, Christina J.</dc:contributor>
    <dc:contributor>Zavolan, Mihaela</dc:contributor>
    <dc:contributor>Artimo, Panu</dc:contributor>
    <dc:creator>Schmidt, Ralf</dc:creator>
    <dc:contributor>Schmidt, Ralf</dc:contributor>
    <dc:creator>Artimo, Panu</dc:creator>
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    <dc:contributor>Kanitz, Alexander</dc:contributor>
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