Prof Richard Baldock, MRC Human Genetics Unit, Edinburgh
The Edinburgh Mouse Atlas and associated gene-expression databases such as Emage emouseatlas.org, GUDMAP gudmap.org and EurExpress www.eurexpress.org provide a unique large-scale image resource with gene-expression spatially mapped onto a standard spatial and ontological framework (Baldock et al., 2003; Richardson et al., 2010). These databases hold about 20TB of image data with expression patterns across the whole genome and is being analysed by a variety of clustering and data-mining techniques. For this data and related projects which have captured very-large image volumes (30-100GB per image volume) we have developed 3D Image servers which can provide tiled-views of high-resolution images at arbitrary re-sectioning angles through the volume (Husz et al., 2009). These “Google-Maps” type interfaces allow very rapid access to large image archives without the need to download large image volumes. These browser-based interfaces are currently being upgraded to include on-line annotation and spatial-mapping using the constrained distance warping techniques developed for cope with the complex embryo transformations needed to map data. The eMouseAtlas programme is collaborating with numbers of laboratories involved with the International Mouse Phenotyping Consortium specifically with respect to capture, analysis and on-line delivery of the embryo data.
The Baldock group is part of the MRC Human Genetics Unit and Institute of Genetics and Molecular Medicine (IGMM) which now holds a significant imaging facility with recent emphasis on live-imaging at the cellular and tissue level and high-throughput automated scanning of slides including tissue arrays. In most cases the image data is analysed using commercial systems such as iVision but increasingly we are switching to using open-source options such as ImageJ. We also as part of the Mouse Atlas programme have significant image-processing software set 3D image reconstruction, spatial data mapping, annotation and analysis. The post-doc at the MRC will undertake development of the image servers to integrate operation with the OMERO image store in order to provide rapid access to large-scale volumetric data for visualisation as well as sub-setting for analysis. With this capability the post-doc will develop the community annotation and spatial mapping tools which will enable cross-comparison and query between data-sets. In addition the post-doc will work with individual IGMM research groups to extend the OMERO analysis capability to time-lapse imaging of whole embryo or tissue, e.g. kidney, development (Sweeney et al., 2008).
Further information is available on the EMAP website