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

ABSTRACT: 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 Kiendl’s statistical relevance index, and the resulting rule set was optimized by pr

ORGANISM(S): Homo sapiens

SUBMITTER: Thomas Häupl 

PROVIDER: E-GEOD-55235 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress