title: Analyzing M-CSF dependent monocyte/macrophage differentiation: expression modes and meta-modes derived from an independent component analysis.
abstract: BACKGROUND
  The analysis of high-throughput gene expression data sets derived from microarray experiments still is a field of extensive investigation. Although new approaches and algorithms are published continuously, mostly conventional methods like hierarchical clustering algorithms or variance analysis tools are used. Here we take a closer look at independent component analysis (ICA) which is already discussed widely as a new analysis approach. However, deep exploration of its applicability and relevance to concrete biological problems is still missing. In this study, we investigate the relevance of ICA in gaining new insights into well characterized regulatory mechanisms of M-CSF dependent macrophage differentiation.
  
  
  RESULTS
  Statistically independent gene expression modes (GEM) were extracted from observed gene expression signatures (GES) through ICA of different microarray experiments. From each GEM we deduced a group of genes, henceforth called sub-mode. These sub-modes were further analyzed with different database query and literature mining tools and then combined to form so called meta-modes. With them we performed a knowledge-based pathway analysis and reconstructed a well known signal cascade.
  
  
  CONCLUSIONS
  We show that ICA is an appropriate tool to uncover underlying biological mechanisms from microarray data. Most of the well known pathways of M-CSF dependent monocyte to macrophage differentiation can be identified by this unsupervised microarray data analysis. Moreover, recent research results like the involvement of proliferation associated cellular mechanisms during macrophage differentiation can be corroborated.
authors.affiliation: Institute for Clinical Chemistry and Laboratory Medicine, University of Regensburg, D-93042 Regensburg, Germany. dominik.lutter@klinik.uni-regensburg.de
authors.forename: Dominik
authors.initials: D
authors.lastname: Lutter
authors.forename: Peter
authors.initials: P
authors.lastname: Ugocsai
authors.forename: Margot
authors.initials: M
authors.lastname: Grandl
authors.forename: Evelyn
authors.initials: E
authors.lastname: Orso
authors.forename: Fabian
authors.initials: F
authors.lastname: Theis
authors.forename: Elmar W
authors.initials: EW
authors.lastname: Lang
authors.forename: Gerd
authors.initials: G
authors.lastname: Schmitz
mesh_terms: D002454:Cell Differentiation; D016207:Cytokines / Q000378:metabolism*; D020869:Gene Expression Profiling / Q000379:methods*; D016173:Macrophage Colony-Stimulating Factor / Q000378:metabolism*; D008264:Macrophages / Q000166:cytology* / Q000378:metabolism*; D015201:Meta-Analysis as Topic; D009000:Monocytes / Q000166:cytology* / Q000378:metabolism*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D025341:Principal Component Analysis; D015398:Signal Transduction / Q000502:physiology
chemical_list: D016207:Cytokines; D016173:Macrophage Colony-Stimulating Factor