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@ARTICLE{Lujumba:304286,
      author       = {I. Lujumba and Y. Adam and H. Ziaei Jam and I. Isewon and
                      N. Monnakgotla and Y. Li and B. Onyido and K. Fredrick and
                      F. Adegoke and J. Emmanuel and J. Adeyemi and O. Ibitoye and
                      S. Owusu-Ansah and M. B. Akanle and H. Joseph and M. Nsubuga
                      and R. Galiwango and M. Okitwi and N. Magdalene and O.
                      Walter and Z. Mngadi and M. Adebiyi and J. Oyelade and M.
                      Nel and D. Jjingo and M. Gymrek and E. F. Adebiyi$^*$},
      title        = {{A} practical guide to identifying associations between
                      tandem repeats and complex human traits using consensus
                      genotypes from multiple tools.},
      journal      = {Nature protocols},
      volume       = {nn},
      issn         = {1754-2189},
      address      = {Basingstoke},
      publisher    = {Nature Publishing Group},
      reportid     = {DKFZ-2025-01826},
      pages        = {nn},
      year         = {2025},
      note         = {#LA:B330# / epub},
      abstract     = {Tandem repeats (TRs) are highly variable loci in the human
                      genome that are linked to various human phenotypes. Accurate
                      and reliable genotyping of TRs is important in understanding
                      population TR variation dynamics and their effects in
                      TR-trait association studies. In this protocol, we describe
                      how to generate high-quality consensus TR genotypes for
                      population genomics studies. In particular, we detail steps
                      to: (i) perform TR genotyping from short-read whole-genome
                      sequencing data by using the HipSTR, GangSTR, adVNTR and
                      ExpansionHunter tools, (ii) perform quality control checks
                      on TR genotypes by using TRTools and (iii) integrate TR
                      genotypes from different tools by using EnsembleTR. We
                      further discuss how to visualize and investigate TR
                      variation patterns to identify population-specific
                      expansions and perform TR-trait association analyses. We
                      demonstrate the utility of these steps by analyzing a small
                      dataset from the 1000 Genomes Project. In addition, we
                      recapitulate a previously identified association between TR
                      length and gene expression in the African population and
                      provide a generalized discussion on TR analysis and its
                      relevance to identifying complex traits. The expected time
                      for installing the necessary software for each section is
                      ~10 min. The expected run time on the user's desired dataset
                      can vary from hours to days depending on factors such as the
                      size of the data, input parameters and the capacity of the
                      computing infrastructure.},
      subtyp        = {Review Article},
      cin          = {B330},
      ddc          = {610},
      cid          = {I:(DE-He78)B330-20160331},
      pnm          = {312 - Funktionelle und strukturelle Genomforschung
                      (POF4-312)},
      pid          = {G:(DE-HGF)POF4-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40890532},
      doi          = {10.1038/s41596-025-01231-y},
      url          = {https://inrepo02.dkfz.de/record/304286},
}