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@ARTICLE{Samannshausen:298229,
      author       = {Z. Saßmannshausen$^*$ and L. M. Blank$^*$ and L.
                      Solé-Boldo$^*$ and F. Lyko$^*$ and G. Raddatz$^*$},
      title        = {esti{MA}ge: development of a {DNA} methylation clock to
                      estimate the methylation age of single cells.},
      journal      = {Bioinformatics advances},
      volume       = {5},
      number       = {1},
      issn         = {2635-0041},
      address      = {Oxford},
      publisher    = {Oxford University Press},
      reportid     = {DKFZ-2025-00236},
      pages        = {vbaf005},
      year         = {2025},
      note         = {#EA:A130#LA:A130# / DKFZ-ZMBH Alliance},
      abstract     = {Since their introduction about 10 years ago, methylation
                      clocks have provided broad insights into the biological age
                      of different species, tissues, and in the context of several
                      diseases or aging. However, their application to single-cell
                      methylation data remains a major challenge, because of the
                      inherent sparsity of such data, as many CpG sites are not
                      covered. A methylation clock applicable on single-cell level
                      could help to further disentangle the processes that drive
                      the ticking of epigenetic clocks.We have developed estiMAge
                      ('estimation of Methylation Age'), a framework that exploits
                      redundancy in methylation data to substitute missing CpGs of
                      trained methylation clocks in single cells. Using Euclidean
                      distance as a measure of similarity, we determine which CpGs
                      covary with the required CpG sites of an epigenetic clock
                      and can be used as surrogates for clock CpGs not covered in
                      single-cell experiments. estiMAge is thus a tool that can be
                      applied to standard epigenetic clocks built on elastic net
                      regression, to achieve bulk and single-cell resolution. We
                      show that estiMAge can accurately predict the ages of young
                      and old hepatocytes and can be used to generate single-cell
                      versions of publicly available epigenetic clocks.The source
                      code and instructions for usage of estiMAge are available at
                      https://github.com/DivEpigenetics/estiMAge.},
      cin          = {A130},
      ddc          = {004},
      cid          = {I:(DE-He78)A130-20160331},
      pnm          = {311 - Zellbiologie und Tumorbiologie (POF4-311)},
      pid          = {G:(DE-HGF)POF4-311},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:39867532},
      pmc          = {pmc:PMC11769677},
      doi          = {10.1093/bioadv/vbaf005},
      url          = {https://inrepo02.dkfz.de/record/298229},
}