Data mining and machine learning approaches for the integration of genome-wide association and methylation data: methodology and main conclusions from GAW20

  • Darst B
  • Engelman C
  • Tian Y
  • et al.
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Abstract

Multiple layers of genetic and epigenetic variability are being simultaneously explored in an increasing number of health studies. We summarize here different approaches applied in the Data Mining and Machine Learning group at the GAW20 to integrate genome-wide genotype and methylation array data.

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Darst, B., Engelman, C. D., Tian, Y., & Lorenzo Bermejo, J. (2018). Data mining and machine learning approaches for the integration of genome-wide association and methylation data: methodology and main conclusions from GAW20. BMC Genetics, 19(S1). https://doi.org/10.1186/s12863-018-0646-3

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