Molecular decomposition of complex clinical phenotypes using biologically structured analysis of microarray data.
BACKGROUND
Today, the characterization of clinical phenotypes by gene-expression patterns is widely used in clinical research. If the investigated phenotype is complex from the molecular point of view, new challenges arise and these have not been addressed systematically. For instance, the same clinical phenotype can be caused by various molecular disorders, such that one observes different characteristic expression patterns in different patients.


RESULTS
In this paper we describe a novel algorithm called Structured Analysis of Microarrays (StAM), which accounts for molecular heterogeneity of complex clinical phenotypes. Our algorithm goes beyond established methodology in several aspects: in addition to the expression data, it exploits functional annotations from the Gene Ontology database to build biologically focussed classifiers. These are used to uncover potential molecular disease subentities and associate them to biological processes without compromising overall prediction accuracy.


BACKGROUND
Bioconductor compliant R package


BACKGROUND
Complete analyses are available at http://compdiag.molgen.mpg.de/supplements/lottaz05.
Lottaz
Claudio
C
Max Planck Institute for Molecular Genetics and Berlin Center for Genome Based Bioinformatics, Germany. Claudio.Lottaz@molgen.mpg.de
Spang
Rainer
R
D014408:Biomarkers, Tumor / Q000145:classification / Q000235:genetics / Q000378:metabolism*; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D005820:Genetic Testing / Q000379:methods*; D006801:Humans; D009323:Natural Language Processing; D009363:Neoplasm Proteins / Q000145:classification / Q000235:genetics / Q000378:metabolism*; D009369:Neoplasms / Q000175:diagnosis / Q000235:genetics / Q000378:metabolism*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010641:Phenotype; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013329:Structure-Activity Relationship
D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins