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Classification based on extensions of LS-PLS using logistic regression: application to clinical and multiple genomic data.

Caroline BazzoliSophie Lambert-Lacroix
Published in: BMC bioinformatics (2018)
In general, those methods using only clinical data or only genomic data perform poorly. The advantage of using LS-PLS methods for classification and their performances are shown and then used to analyze clinical and genomic data. The corresponding prediction results are encouraging and stable regardless of the data set and/or number of selected features. These extensions have been implemented in the R package lsplsGlm to enhance their use.
Keyphrases
  • electronic health record
  • big data
  • machine learning
  • copy number
  • deep learning
  • gene expression
  • dna methylation
  • genome wide