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A comparison of automatic cell identification methods for single-cell RNA-sequencing data

Tamim Abdelaal; Lieke Michielsen; Davy Cats; Dylan Hoogduin; Hailiang Mei; Marcel Reinders; Ahmed Mahfouz


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  <identifier identifierType="DOI">10.5281/zenodo.3357167</identifier>
  <creators>
    <creator>
      <creatorName>Tamim Abdelaal</creatorName>
      <affiliation>Delft university of technology</affiliation>
    </creator>
    <creator>
      <creatorName>Lieke Michielsen</creatorName>
      <affiliation>Delft university of technology</affiliation>
    </creator>
    <creator>
      <creatorName>Davy Cats</creatorName>
      <affiliation>Leiden University Medical Center</affiliation>
    </creator>
    <creator>
      <creatorName>Dylan Hoogduin</creatorName>
      <affiliation>Leiden University Medical Center</affiliation>
    </creator>
    <creator>
      <creatorName>Hailiang Mei</creatorName>
      <affiliation>Leiden University Medical Center</affiliation>
    </creator>
    <creator>
      <creatorName>Marcel Reinders</creatorName>
      <affiliation>Delft university of technology</affiliation>
    </creator>
    <creator>
      <creatorName>Ahmed Mahfouz</creatorName>
      <affiliation>Leiden University Medical Center</affiliation>
    </creator>
  </creators>
  <titles>
    <title>A comparison of automatic cell identification methods for single-cell RNA-sequencing data</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>scRNA-seq</subject>
    <subject>Benchmark</subject>
    <subject>Classification</subject>
    <subject>Cell identity</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2019-08-01</date>
  </dates>
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  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Benchmark datasets used to evaluate the performance of 22 classifiers for cell type classification for scRNA-seq data&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/675743/">675743</awardNumber>
      <awardTitle>Image-Guided Surgery (IGS) and Personalised Postoperative Immunotherapy To Improving Cancer Outcome</awardTitle>
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