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@ARTICLE{Lin:292290,
      author       = {H.-Y. Lin and H. Mazumder and I. Sarkar and P.-Y. Huang and
                      R. A. Eeles and Z. Kote-Jarai and K. R. Muir and J.
                      Schleutker and N. Pashayan and J. Batra and D. E. Neal and
                      S. F. Nielsen and B. G. Nordestgaard and H. Grönberg and F.
                      Wiklund and R. J. MacInnis and C. A. Haiman and R. C. Travis
                      and J. L. Stanford and A. S. Kibel and C. Cybulski and K.-T.
                      Khaw and C. Maier and S. N. Thibodeau and M. R. Teixeira and
                      L. Cannon-Albright and H. Brenner$^*$ and R. Kaneva and H.
                      Pandha and J. Y. Park},
      collaboration = {UKGPCS collaborators and APCB and P. consortium},
      title        = {{C}luster effect for {SNP}-{SNP} interaction pairs for
                      predicting complex traits.},
      journal      = {Scientific reports},
      volume       = {14},
      number       = {1},
      issn         = {2045-2322},
      address      = {[London]},
      publisher    = {Macmillan Publishers Limited, part of Springer Nature},
      reportid     = {DKFZ-2024-01651},
      pages        = {18677},
      year         = {2024},
      abstract     = {Single nucleotide polymorphism (SNP) interactions are the
                      key to improving polygenic risk scores. Previous studies
                      reported several significant SNP-SNP interaction pairs that
                      shared a common SNP to form a cluster, but some identified
                      pairs might be false positives. This study aims to identify
                      factors associated with the cluster effect of false
                      positivity and develop strategies to enhance the accuracy of
                      SNP-SNP interactions. The results showed the cluster effect
                      is a major cause of false-positive findings of SNP-SNP
                      interactions. This cluster effect is due to high
                      correlations between a causal pair and null pairs in a
                      cluster. The clusters with a hub SNP with a significant main
                      effect and a large minor allele frequency (MAF) tended to
                      have a higher false-positive rate. In addition, peripheral
                      null SNPs in a cluster with a small MAF tended to enhance
                      false positivity. We also demonstrated that using the
                      modified significance criterion based on the 3 p-value rules
                      and the bootstrap approach (3pRule + bootstrap) can reduce
                      false positivity and maintain high true positivity. In
                      addition, our results also showed that a pair without a
                      significant main effect tends to have weak or no
                      interaction. This study identified the cluster effect and
                      suggested using the 3pRule + bootstrap approach to enhance
                      SNP-SNP interaction detection accuracy.},
      keywords     = {Polymorphism, Single Nucleotide / Humans / Multifactorial
                      Inheritance: genetics / Gene Frequency / Genome-Wide
                      Association Study: methods / Cluster Analysis / Models,
                      Genetic / Epistasis, Genetic / Cluster (Other) / False
                      positivity (Other) / SNP interaction (Other) / Simulation
                      (Other)},
      cin          = {C070 / C120 / HD01},
      ddc          = {600},
      cid          = {I:(DE-He78)C070-20160331 / I:(DE-He78)C120-20160331 /
                      I:(DE-He78)HD01-20160331},
      pnm          = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
      pid          = {G:(DE-HGF)POF4-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:39134575},
      doi          = {10.1038/s41598-024-66311-7},
      url          = {https://inrepo02.dkfz.de/record/292290},
}