github link
Accession IconGSE55235

Identification of rheumatoid arthritis and osteoarthritis patients by transcriptome-based rule set generation

Organism Icon Homo sapiens
Sample Icon 29 Downloadable Samples
Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Submitter Supplied Information

Description
Discrimination of rheumatoid arthritis (RA) patients from patients with other inflammatory/degenerative joint diseases or healthy individuals purely on the basis of genes differentially expressed in high-throughput data has proven very difficult. Thus, the present study sought to achieve such discrimination by employing a novel unbiased approach using rule-based classifiers. Three multi-center genome-wide transcriptomic data sets (Affymetrix HG- U133 A/B) from a total of 79 individuals, including 20 healthy controls (control group - CG), as well as 26 osteoarthritis (OA) and 33 RA patients, were used to infer rule- based classifiers to discriminate the disease groups. The rules were ranked with respect to Kiendls statistical relevance index, and the resulting rule set was optimized by pruning. The rule sets were inferred separately from data of one of three centers and applied to the two remaining centers for validation. All rules from the optimized rule sets of all centers were used to analyze their biological relevance applying the software Pathway Studio.
PubMed ID
Total Samples
30
Submitter’s Institution
Alternate Accession IDs

Samples

Show of 0 Total Samples
Filter
Add/Remove
Accession Code
Title
Specimen part
Disease
Disease stage
Processing Information
Additional Metadata
No rows found
Loading...