A tool for identification of genes expressed in patterns of interest using the Allen Brain Atlas

Motivation: Gene expression patterns can be useful in understanding the structural organization of the brain and the regulatory logic that governs its myriad cell types. A particularly rich source of spatial expression data is the Allen Brain Atlas (ABA), a comprehensive genome-wide in situ hybridization study of the adult mouse brain. Here, we present an open-source program, ALLENMINER, that searches the ABA for genes that are expressed, enriched, patterned or graded in a user-specified region of interest. Results: Regionally enriched genes identified by ALLENMINER accurately reflect the in situ data (95-99% concordance with manual curation) and compare with regional microarray studies as expected from previous comparisons (61-80% concordance). We demonstrate the utility of ALLENMINER by identifying genes that exhibit patterned expression in the caudoputamen and neocortex. We discuss general characteristics of gene expression in the mouse brain and the potential application of ALLENMINER to design strategies for specific genetic access to brain regions and cell types.