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Detection of suspicious interactions of spiking covariates in methylation data.

Miriam SiegGesa RichterArne S SchaeferJochen Kruppa
Published in: BMC bioinformatics (2020)
We help to check for the validation of the linear regression assumptions in a methylation analysis pipeline. These assumptions should also be considered for machine learning approaches. In addition, we are able to detect outliers in the continuous covariate. Therefore, more statistical robust results should be produced in methylation analysis using our algorithm as a preprocessing step.
Keyphrases
  • machine learning
  • genome wide
  • dna methylation
  • big data
  • deep learning
  • artificial intelligence
  • electronic health record