title: Exploring the transcription factor activity in high-throughput gene expression data using RLQ analysis.
abstract: BACKGROUND
  Interpretation of gene expression microarray data in the light of external information on both columns and rows (experimental variables and gene annotations) facilitates the extraction of pertinent information hidden in these complex data. Biologists classically interpret genes of interest after retrieving functional information from a subset of genes of interest. Transcription factors play an important role in orchestrating the regulation of gene expression. Their activity can be deduced by examining the presence of putative transcription factors binding sites in the gene promoter regions.
  
  
  RESULTS
  In this paper we present the multivariate statistical method RLQ which aims to analyze microarray data where additional information is available on both genes and samples. As an illustrative example, we applied RLQ methodology to analyze transcription factor activity associated with the time-course effect of steroids on the growth of primary human lung fibroblasts. RLQ could successfully predict transcription factor activity, and could integrate various other sources of external information in the main frame of the analysis. The approach was validated by means of alternative statistical methods and biological validation.
  
  
  CONCLUSIONS
  RLQ provides an efficient way of extracting and visualizing structures present in a gene expression dataset by directly modeling the link between experimental variables and gene annotations.
authors.affiliation: Division of Pulmonary Medicine, Cantonal Hospital St, Gallen, Rorschacherstrasse 95, CH-9007 St, Gallen, Switzerland. florent.baty@kssg.ch
authors.forename: Florent
authors.initials: F
authors.lastname: Baty
authors.forename: Jochen
authors.initials: J
authors.lastname: Rüdiger
authors.forename: Nicola
authors.initials: N
authors.lastname: Miglino
authors.forename: Lukas
authors.initials: L
authors.lastname: Kern
authors.forename: Peter
authors.initials: P
authors.lastname: Borger
authors.forename: Martin
authors.initials: M
authors.lastname: Brutsche
mesh_terms: D001665:Binding Sites; D049109:Cell Proliferation / Q000187:drug effects; D005347:Fibroblasts / Q000166:cytology / Q000187:drug effects / Q000378:metabolism; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D008168:Lung / Q000166:cytology; D058977:Molecular Sequence Annotation; D000068656:Mometasone Furoate; D015999:Multivariate Analysis; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011244:Pregnadienediols / Q000494:pharmacology; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D011244:Pregnadienediols; D014157:Transcription Factors; D000068656:Mometasone Furoate