Analyzing in situ gene expression in the mouse brain with image registration, feature extraction and block clustering

Background: Many important high throughput projects use in situ hybridization and may require the analysis of images of spatial cross sections of organisms taken with cellular level resolution. Projects creating gene expression atlases at unprecedented scales for the embryonic fruit fly as well as the embryonic and adult mouse already involve the analysis of hundreds of thousands of high resolution experimental images mapping mRNA expression patterns. Challenges include accurate registration of highly deformed tissues, associating cells with known anatomical regions, and identifying groups of genes whose expression is coordinately regulated with respect to both concentration and spatial location. Solutions to these and other challenges will lead to a richer understanding of the complex system aspects of gene regulation in heterogeneous tissue. Results: We present an end-to-end approach for processing raw in situ expression imagery and performing subsequent analysis. We use a non-linea...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Manjunatha Jagalur, Chris Pal, Erik G. Learned-Miller, R. Thomas Zoeller, David Kulp
• Keywords: Anatomical Region, BMCBI 2007, Gene, Image