Abstract
AbstractBackgroundThe spatio-temporal organisation of many biological processes such as gene-expression and neuronal activity is critical to understanding the overall biological behaviour, phenotype and disease. This is especially true during embryonic development. During development spatial patterns of gene expression are key to segmentation, tissue differentiation and organ development. In situ techniques can reveal the activity of genes and the presence of proteins to a very high sub-cellular resolution but typically at high resolution only a few probes can be used on any sample therefore to compare many such patterns requires mapping of image-based data to a standard spatial framework. Once mapped those data can be collated, queried and analysed in purely spatial terms to reveal unknown combinatorial gene-activity that could not be discovered any other way. Mapping spatial data to image domains with systematic variation in shape and pose, such as embryos or elongated organs, presents special problems. Automated techniques available for more constrained systems can not deliver the mapping fidelity required to analyse these data therefore we have developed a manual editing tool, WlzWarp, for mapping 3D image data using the constrained distance transform (CDT) which uniquely can deliver the complex transforms required.ResultsWe have implemented a fully open-source tool (available on GitHub), WlzWarp to provide interactive complex spatial mapping of 3D image data. We have applied WlzWarp to map a set of gene-expression patterns in the developing mouse embryo that could not be mapped by any other technique. The transform procedure was tested by using multiple images of the same gene from independent samples and thereby testing the full end-to-end mapping process. WlzWarp is implemented in C++ using open-source packages Qt, Coin and SIMVoleon for cross-architecture compatibility. It has been developed under Linux but also tested on Mac OSX and MS Windows.ConclusionsWlzWarp is a freely available software tool for non-linear registration and alignment of complex 2D & 3D spatial patterns from one image to another or to an atlas model. It has been tested in the context of embryo data but can be used for any 3D or 2D image registration problem.
Publisher
Cold Spring Harbor Laboratory
Reference20 articles.
1. A Database for Mouse Development
2. The mouse atlas and graphical gene-expression database
3. Baldock, R.A. , Dubreuil, C. , Hill, B. , Davidson, D. : The Edinburgh Mouse Atlas: Basic Structure and Informatics. In: Levotsky, S. (ed.) Bioinformatics Databases and Systems, pp. 102–115. Kluwer Academic Press, ??? (1999)
4. Davidson, D. , Baldock, R. : Bioinformatics beyond sequence: mapping gene function in the embryo. Nature Reviews Genetics (2001)
5. EMAGE mouse embryo spatial gene expression database: 2014 update
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献