title: Disease-specific genomic analysis: identifying the signature of pathologic biology.
abstract: BACKGROUND
  Genomic high-throughput technology generates massive data, providing opportunities to understand countless facets of the functioning genome. It also raises profound issues in identifying data relevant to the biology being studied.
  
  
  RESULTS
  We introduce a method for the analysis of pathologic biology that unravels the disease characteristics of high dimensional data. The method, disease-specific genomic analysis (DSGA), is intended to precede standard techniques like clustering or class prediction, and enhance their performance and ability to detect disease. DSGA measures the extent to which the disease deviates from a continuous range of normal phenotypes, and isolates the aberrant component of data. In several microarray cancer datasets, we show that DSGA outperforms standard methods. We then use DSGA to highlight a novel subdivision of an important class of genes in breast cancer, the estrogen receptor (ER) cluster. We also identify new markers distinguishing ductal and lobular breast cancers. Although our examples focus on microarrays, DSGA generalizes to any high dimensional genomic/proteomic data.
authors.affiliation: Department of Surgery, Stanford University School of Medicine, Stanford University, Stanford, CA, USA.
authors.forename: Monica
authors.initials: M
authors.lastname: Nicolau
authors.forename: Robert
authors.initials: R
authors.lastname: Tibshirani
authors.forename: Anne-Lise
authors.initials: AL
authors.lastname: Børresen-Dale
authors.forename: Stefanie S
authors.initials: SS
authors.lastname: Jeffrey
mesh_terms: D014408:Biomarkers, Tumor / Q000235:genetics*; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D002874:Chromosome Mapping / Q000379:methods*; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods; D005819:Genetic Markers / Q000235:genetics*; D006801:Humans; D009363:Neoplasm Proteins / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011960:Receptors, Estrogen / Q000235:genetics*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor; D005819:Genetic Markers; D009363:Neoplasm Proteins; D011960:Receptors, Estrogen