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Comparison of methods for the detection of outliers and associated biomarkers in mislabeled omics data.

Hongwei SunYuehua CuiHui WangHaixia LiuTong Wang
Published in: BMC bioinformatics (2020)
When the proportion of outliers is ≤5%, Ensemble can be used for variable selection. When the proportion of outliers is > 5%, Ensemble can be used for variable selection on a subset after removing outliers identified by enetLTS. For outlier identification, enetLTS is the recommended method. In practice, the proportion of outliers can be estimated according to the inaccuracy of the diagnostic methods used.
Keyphrases
  • primary care
  • convolutional neural network
  • single cell
  • neural network
  • loop mediated isothermal amplification
  • deep learning