title: Visualisation of the T cell differentiation programme by Canonical Correspondence Analysis of transcriptomes.
abstract: BACKGROUND
  Currently, in the era of post-genomics, immunology is facing a challenging problem to translate mutant phenotypes into gene functions based on high-throughput data, while taking into account the classifications and functions of immune cells, which requires new methods.
  
  
  RESULTS
  Here we propose a novel application of a multidimensional analysis, Canonical Correspondence Analysis (CCA), to reveal the molecular characteristics of undefined cells in terms of cellular differentiation programmes by analysing two transcriptomic datasets. Using two independent datasets, whether RNA-seq or microarray data, CCA successfully visualised the cross-level relationships between genes, cells, and differentiation programmes, and thereby identified the immunological features of mutant cells (Gata3-KO T cells and Stat3-KO T cells) in a data-oriented manner. With a new concept, differentiation variable, CCA provides an automatic classification of cell samples, which had a high sensitivity and a comparable performance to other classification methods. In addition, we elaborate how CCA results can be interpreted, and reveal the features of CCA in comparison with other visualisation techniques.
  
  
  CONCLUSIONS
  CCA is a visualisation tool with a classification ability to reveal the cross-level relationships of genes, cells and differentiation programmes. This can be used for characterising the functional defect of cells of interest (e.g. mutant cells) in the context of cellular differentiation. The proposed approach fits with common hypothesis-oriented studies in immunology, and can be used for a wide range of molecular and genomic studies on cellular differentiation mechanisms.
authors.affiliation: Immunobiology Section, UCL Institute of Child Health, University College London, 30 Guilford Street, London WC1N 1EH, UK. m.ono@ucl.ac.uk.
authors.forename: Masahiro
authors.initials: M
authors.lastname: Ono
authors.forename: Reiko J
authors.initials: RJ
authors.lastname: Tanaka
authors.forename: Manabu
authors.initials: M
authors.lastname: Kano
mesh_terms: D000818:Animals; D002454:Cell Differentiation / Q000235:genetics*; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D066264:Datasets as Topic; D050990:GATA3 Transcription Factor / Q000235:genetics; D017353:Gene Deletion; D020869:Gene Expression Profiling; D055786:Gene Knockout Techniques; D051379:Mice; D016176:T-Lymphocyte Subsets / Q000166:cytology / Q000276:immunology / Q000378:metabolism; D013601:T-Lymphocytes / Q000166:cytology* / Q000276:immunology / Q000378:metabolism*; D059467:Transcriptome
chemical_list: D050990:GATA3 Transcription Factor