title: Integrative phenotyping framework (iPF): integrative clustering of multiple omics data identifies novel lung disease subphenotypes.
abstract: BACKGROUND
  The increased multi-omics information on carefully phenotyped patients in studies of complex diseases requires novel methods for data integration. Unlike continuous intensity measurements from most omics data sets, phenome data contain clinical variables that are binary, ordinal and categorical.
  
  
  RESULTS
  In this paper we introduce an integrative phenotyping framework (iPF) for disease subtype discovery. A feature topology plot was developed for effective dimension reduction and visualization of multi-omics data. The approach is free of model assumption and robust to data noises or missingness. We developed a workflow to integrate homogeneous patient clustering from different omics data in an agglomerative manner and then visualized heterogeneous clustering of pairwise omics sources. We applied the framework to two batches of lung samples obtained from patients diagnosed with chronic obstructive lung disease (COPD) or interstitial lung disease (ILD) with well-characterized clinical (phenomic) data, mRNA and microRNA expression profiles. Application of iPF to the first training batch identified clusters of patients consisting of homogenous disease phenotypes as well as clusters with intermediate disease characteristics. Analysis of the second batch revealed a similar data structure, confirming the presence of intermediate clusters. Genes in the intermediate clusters were enriched with inflammatory and immune functional annotations, suggesting that they represent mechanistically distinct disease subphenotypes that may response to immunomodulatory therapies. The iPF software package and all source codes are publicly available.
  
  
  CONCLUSIONS
  Identification of subclusters with distinct clinical and biomolecular characteristics suggests that integration of phenomic and other omics information could lead to identification of novel mechanism-based disease sub-phenotypes.
authors.affiliation: Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, 15261, USA. swiss747@gmail.com.|Department of Statistics, Korea University, Seoul, 5062, South Korea. swiss747@gmail.com.
authors.forename: SungHwan
authors.initials: S
authors.lastname: Kim
authors.affiliation: Department of Internal Medicine (Pulmonary, Critical Care and Sleep Medicine), Yale School of Medicine, New Haven, CT, 06520, USA. jose.herazo-maya@yale.edu.
authors.forename: Jose D
authors.initials: JD
authors.lastname: Herazo-Maya
authors.affiliation: Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA. donkang75@gmail.com.
authors.forename: Dongwan D
authors.initials: DD
authors.lastname: Kang
authors.affiliation: Department of Internal Medicine (Pulmonary, Critical Care and Sleep Medicine), Yale School of Medicine, New Haven, CT, 06520, USA. brendyjuan@hotmail.com.
authors.forename: Brenda M
authors.initials: BM
authors.lastname: Juan-Guardela
authors.affiliation: Department of Medicine, University of Pittsburgh, Pittsburgh, PA, 15261, USA. tedrowjr@upmc.edu.
authors.forename: John
authors.initials: J
authors.lastname: Tedrow
authors.affiliation: Department of Medicine, Weill Cornell Medical College, New York, NY, 15261, USA. fjm2003@med.cornell.edu.
authors.forename: Fernando J
authors.initials: FJ
authors.lastname: Martinez
authors.affiliation: Department of Medicine, University of Pittsburgh, Pittsburgh, PA, 15261, USA. sciurbafc@upmc.edu.
authors.forename: Frank C
authors.initials: FC
authors.lastname: Sciurba
authors.affiliation: Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, 15261, USA. ctseng@pitt.edu.|Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, 15261, USA. ctseng@pitt.edu.
authors.forename: George C
authors.initials: GC
authors.lastname: Tseng
authors.affiliation: Department of Internal Medicine (Pulmonary, Critical Care and Sleep Medicine), Yale School of Medicine, New Haven, CT, 06520, USA. naftali.kaminski@yale.edu.
authors.forename: Naftali
authors.initials: N
authors.lastname: Kaminski
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D066264:Datasets as Topic; D016002:Discriminant Analysis; D023281:Genomics / Q000379:methods; D006801:Humans; D008171:Lung Diseases / Q000209:etiology / Q000378:metabolism; D058977:Molecular Sequence Annotation; D010641:Phenotype; D057188:Workflow