The MAQC-II Project: A comprehensive study of common practices for the development and validation of microarray-based predictive models
Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.
Sex, Age, Specimen part, Race, Compound
View SamplesThe Hamner data set (endpoint A) was provided by The Hamner Institutes for Health Sciences (Research Triangle Park, NC, USA). The study objective was to apply microarray gene expression data from the lung of female B6C3F1 mice exposed to a 13-week treatment of chemicals to predict increased lung tumor incidence in the 2-year rodent cancer bioassays of the National Toxicology Program. If successful, the results may form the basis of a more efficient and economical approach for evaluating the carcinogenic activity of chemicals. Microarray analysis was performed using Affymetrix Mouse Genome 430 2.0 arrays on three to four mice per treatment group, and a total of 70 mice were analyzed and used as the MAQC-II's training set (GEO Series GSE6116). Additional data from another set of 88 mice were collected later and provided as the MAQC-II's external validation set (this Series). The training dataset had already been deposited in GEO by its provider and its accession number is GSE6116.
Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.
Specimen part, Compound
View SamplesGlucocorticoids (GC) are used as first line therapies for generalized suppression of inflammation (e.g. allergies or autoimmune diseases), but their long-term use is limited by severe side effects. Our previous work has revealed that GC induced a stable anti-inflammatory phenotype in monocytes, the glucocorticoid-stimulated monocytes (GCsM) that we now exploited for targeted GC-mediated therapeutic effects.
Immune suppression via glucocorticoid-stimulated monocytes: a novel mechanism to cope with inflammation.
Specimen part, Treatment
View Samples