The Processing and Analysis of in situ Gene Expression Images of the Mouse Brain

 

Manjunatha N. Jagalur1, Chris Pal1*, Erik Learned-Miller1, R. T. Zoeller2 and David Kulp1

1Department of Computer Science,

2Department of Biology & The Laboratory of Molecular and Cellular Neurobiology

University of Massachusetts, Amherst, MA 01003

*Contact author: pal@cs.umass.edu

 

 

Abstract

 

Many important high throughput projects are now underway which use in situ gene expression detection technology and require the analysis of images of spatial cross sections of organisms taken at cellular level resolution. Projects creating atlases for the embryonic fruit fly, embryonic and adult mouse at an unprecedented genomic scale already involve the analysis of hundreds of thousands of high resolution experimental images. We present an end-to-end approach for processing raw images and performing analysis. We use a non-linear image registration technique specifically adapted for mapping expression images to anatomical annotations and a method for extracting expression information. We also present a new approach for jointly clustering the rows and columns of a matrix and we relate clustered patterns to Gene Ontology (GO) annotations. Our approach should be more broadly applicable to other in situ experiments but we focus our analysis here on imagery and experiments of the mouse brain an application with tremendous potential for increasing our fundamental understanding of neural information processing systems.

 

 

Keywords

 

Image registration, Mutual Information, Bi-clustering, in situ gene expression, high throughput, bioinformatics.

 

 

Citation

 

Manjunatha N. Jagalur, Chris Pal, Erik Learned-Miller, R. T. Zoeller and David Kulp. (2007) Analyzing in situ Gene Expression in the Mouse Brain with Image Registration, Feature Extraction and Block Clustering BMC Bioinformatics vol. 8, suppl. 10, Dec. 21.

Manjunatha N. Jagalur, Chris Pal, Erik Learned-Miller, R. T. Zoeller and David Kulp.
(2006) The Processing and Analysis of in situ Gene Expression Images of the Mouse Brain. In Advances in Neural Information Processing Systems (NIPS) Workshop on New Problems and Methods in Computational Biology.

 

Paper in PDF format, here (Note: File is 25 MB).

 

 

Illustrative Results

 

 

Step 1: Image Registration

 

Red channel is the expression image, green channel is the reference image. (Left) Before registration. (Middle) After approximate registration. (Right) After our adaptive

non-linear registration step anatomical patterns are extracted using a mask (shown in blue).

 

 

 

Step 2: Analysis via row column clustering.