Bayesian Analysis of Gene Expression Levels (BAGEL) is a program that allows statistical inferences to be made regarding differential gene expression between two or more samples measured on spotted (two-channel) microarrays. BAGEL makes these inferences from normalized ratio data, on a gene-by-gene basis. The advantages of BAGEL include ease of use, straightforward interpretation of results, statistical robustness, flexibility in accepting different experimental designs, and that it is free.