title: GLAD: a mixed-membership model for heterogeneous tumor subtype classification.
abstract: BACKGROUND
  Genomic analyses of many solid cancers have demonstrated extensive genetic heterogeneity between as well as within individual tumors. However, statistical methods for classifying tumors by subtype based on genomic biomarkers generally entail an all-or-none decision, which may be misleading for clinical samples containing a mixture of subtypes and/or normal cell contamination.
  
  
  RESULTS
  We have developed a mixed-membership classification model, called glad, that simultaneously learns a sparse biomarker signature for each subtype as well as a distribution over subtypes for each sample. We demonstrate the accuracy of this model on simulated data, in-vitro mixture experiments, and clinical samples from the Cancer Genome Atlas (TCGA) project. We show that many TCGA samples are likely a mixture of multiple subtypes.
  
  
  BACKGROUND
  A python module implementing our algorithm is available from http://genomics.wpi.edu/glad/.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USA, School of Science and Engineering, Al Akhawayn University, Ifrane, 53000, Morocco, Department of Statistics, University of California, Berkeley, CA 94720, USA, and Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USA, School of Science and Engineering, Al Akhawayn University, Ifrane, 53000, Morocco, Department of Statistics, University of California, Berkeley, CA 94720, USA, and Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
authors.forename: Hachem
authors.initials: H
authors.lastname: Saddiki
authors.affiliation: Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USA, School of Science and Engineering, Al Akhawayn University, Ifrane, 53000, Morocco, Department of Statistics, University of California, Berkeley, CA 94720, USA, and Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
authors.forename: Jon
authors.initials: J
authors.lastname: McAuliffe
authors.affiliation: Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USA, School of Science and Engineering, Al Akhawayn University, Ifrane, 53000, Morocco, Department of Statistics, University of California, Berkeley, CA 94720, USA, and Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USA, School of Science and Engineering, Al Akhawayn University, Ifrane, 53000, Morocco, Department of Statistics, University of California, Berkeley, CA 94720, USA, and Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
authors.forename: Patrick
authors.initials: P
authors.lastname: Flaherty
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000235:genetics*; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D006801:Humans; D009369:Neoplasms / Q000145:classification* / Q000235:genetics*; D012984:Software
chemical_list: D014408:Biomarkers, Tumor