Joint Analysis of In-situ Hybridization and Gene Expression Data

Abstract

To understand transcriptional regulation during development a detailed analysis of gene expression is needed. In-situ hybridization experiments measure the spatial distribution of mRNA-molecules and thus complement DNA-microarray experiments. This is of very high biological relevance, as co-location is a necessary condition for possible molecular interactions.

We use publicly available in-situ data from embryonal development of Drosophila and derive a co-location index for pairs of genes. Our image processing pipeline for in-situ images provides a simpler alternative for the image processing part at comparable performance compared to published prior work. We formulate a mixture model which can use the pair-wise co-location indices as constraints in a mixture estimation on gene expression time-courses.