title: Early immunologic correlates of HIV protection can be identified from computational analysis of complex multivariate T-cell flow cytometry assays.
abstract: BACKGROUND
  Polychromatic flow cytometry (PFC), has enormous power as a tool to dissect complex immune responses (such as those observed in HIV disease) at a single cell level. However, analysis tools are severely lacking. Although high-throughput systems allow rapid data collection from large cohorts, manual data analysis can take months. Moreover, identification of cell populations can be subjective and analysts rarely examine the entirety of the multidimensional dataset (focusing instead on a limited number of subsets, the biology of which has usually already been well-described). Thus, the value of PFC as a discovery tool is largely wasted.
  
  
  RESULTS
  To address this problem, we developed a computational approach that automatically reveals all possible cell subsets. From tens of thousands of subsets, those that correlate strongly with clinical outcome are selected and grouped. Within each group, markers that have minimal relevance to the biological outcome are removed, thereby distilling the complex dataset into the simplest, most clinically relevant subsets. This allows complex information from PFC studies to be translated into clinical or resource-poor settings, where multiparametric analysis is less feasible. We demonstrate the utility of this approach in a large (n=466), retrospective, 14-parameter PFC study of early HIV infection, where we identify three T-cell subsets that strongly predict progression to AIDS (only one of which was identified by an initial manual analysis).
  
  
  BACKGROUND
  The 'flowType: Phenotyping Multivariate PFC Assays' package is available through Bioconductor. Additional documentation and examples are available at: www.terryfoxlab.ca/flowsite/flowType/
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
  
  
  BACKGROUND
  rbrinkman@bccrc.ca.
authors.affiliation: Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC V5Z 1L3, Canada.
authors.forename: Nima
authors.initials: N
authors.lastname: Aghaeepour
authors.forename: Pratip K
authors.initials: PK
authors.lastname: Chattopadhyay
authors.forename: Anuradha
authors.initials: A
authors.lastname: Ganesan
authors.forename: Kieran
authors.initials: K
authors.lastname: O'Neill
authors.forename: Habil
authors.initials: H
authors.lastname: Zare
authors.forename: Adrin
authors.initials: A
authors.lastname: Jalali
authors.forename: Holger H
authors.initials: HH
authors.lastname: Hoos
authors.forename: Mario
authors.initials: M
authors.lastname: Roederer
authors.forename: Ryan R
authors.initials: RR
authors.lastname: Brinkman
mesh_terms: D015415:Biomarkers / Q000032:analysis; D019295:Computational Biology / Q000379:methods*; D005434:Flow Cytometry; D015658:HIV Infections / Q000276:immunology*; D006801:Humans; D016130:Immunophenotyping / Q000379:methods; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D012189:Retrospective Studies; D016176:T-Lymphocyte Subsets / Q000166:cytology / Q000276:immunology*
chemical_list: D015415:Biomarkers