Fitting Gaussian mixture models on incomplete data

HIGHLIGHTS

• who: Zachary R. McCaw from the School of Public Health, Harvard Boston, MA, USA have published the paper: Fitting Gaussian mixture models on incomplete data, in the Journal: (JOURNAL)
• what: Using three case studies on real and simulated 'omics data sets the authors demonstrate that when the underlying data distribution is nearto a GMM MGMM is more effective at recovering the true cluster assignments than either the existing GMM implementations that accommodate missing data or fitting a standard GMM after state of the art imputation.
• how: GWAS summary statistics Finally the authors considered . . .
  

   

  

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