[NOTICE: This data set has been deprecated. Please see our new version of the data (and additional data sets) here: https://osf.io/mhk93 ]
"Barrett’s esophagus (BE) is a metaplastic precursor lesion of esophageal adenocarcinoma (EA), the most rapidly increasing cancer in western societies. While the prevalence of BE is increasing, the vast majority of EA occurs in patients with undiagnosed BE. Thus, we sought to identify genes that are altered in BE compared to the normal mucosa of the esophagus, and which may be potential biomarkers for the development or diagnosis of BE."
We have included gene-expression data, the outcome (class) being predicted, and any clinical covariates. When gene-expression data were processed in multiple batches, we have provided batch information. Each data set is organized into a file set, where each contains all pertinent files for an individual dataset. The gene expression files have been normalized using both the SCAN and UPC methods using the SCAN.UPC package in Bioconductor (https://www.bioconductor.org/packages/release/bioc/html/SCAN.UPC.html). We summarized the data at the gene level using the BrainArray resource (http://brainarray.mbni.med.umich.edu/Brainarray/Database/CustomCDF/20.0.0/ensg.asp). We used Ensembl identifiers. The class, clinical, and batch data were hand curated to ensure consistency ("tidy data" formatting). In addition, the data files have been formatted to be imported easily into the ML-Flex machine learning package (http://mlflex.sourceforge.net/).