ABSTRACT
Pathologists need to compare histopathological images of normal and diseased tissues between different samples, cases, and species. We have designed an interactive system, termed Comparative Pathology Workbench (CPW), which allows direct and dynamic comparison of images at a variety of magnifications, selected regions of interest, as well as the results of image analysis or other data analyses such as scRNA-seq. This allows pathologists to indicate key diagnostic features, with a mechanism to allow discussion threads amongst expert groups of pathologists and other disciplines. The data and associated discussions can be accessed online from anywhere in the world. The Comparative Pathology Workbench (CPW) is a web-browser-based visual analytics platform providing shared access to an interactive "spreadsheet" style presentation of image and associated analysis data. The CPW provides a grid layout of rows and columns so that images that correspond to matching data can be organised in the form of an image-enabled "spreadsheet". An individual workbench can be shared with other users with read-only or full edit access as required. In addition, each workbench element or the whole bench itself has an associated discussion thread to allow collaborative analysis and consensual interpretation of the data. The CPW is a Django-based web-application that hosts the workbench data, manages users, and user-preferences. All image data are hosted by other resource applications such as OMERO or the Digital Slide Archive. Further resources can be added as required. The discussion threads are managed using WordPress and include additional graphical and image data. The CPW has been developed to allow integration of image analysis outputs from systems such as QuPath or ImageJ. All software is open-source and available from a GitHub repository.
ABSTRACT
BACKGROUND: The Edinburgh Mouse Atlas Project (EMAP) ontology of mouse developmental anatomy provides a standard nomenclature for describing normal and mutant mouse embryo anatomy. The ontology forms the core of the EMAP atlas and is used for annotating gene expression data by the mouse Gene Expression Database (GXD), Edinburgh Mouse Atlas of Gene Expression (EMAGE) and other database resources. FINDINGS: The original EMAP ontology listed anatomical entities for each developmental stage separately, presented as uniparental graphs organized as a strict partonomy. An "abstract" (i.e. non-stage-specific) representation of mouse developmental anatomy has since been developed. In this version (EMAPA) all instances for a given anatomical entity are presented as a single term, together with the first and last stage at which it is considered to be present. Timed-component anatomies are now derived using staging information in the "primary" non-timed version. Anatomical entities are presented as a directed acyclic graph enabling multiple parental relationships. Subsumption classification as well as partonomic and other types of relationships can now be represented. Most concept names are unique, with compound names constructed using standardized nomenclature conventions, and alternative names associated as synonyms. CONCLUSIONS: The ontology has been extended and refined in a collaborative effort between EMAP and GXD, with additional input from others. Efforts are also underway to improve the revision process with regards to updating and editorial control. The revised EMAPA ontology is freely available from the OBO Foundry resource, with descriptive information and other documentation presented in associated Wiki pages (http://www.obofoundry.org/wiki/index.php/EMAPA:Main_Page).
ABSTRACT
The precise control of gene expression is critical in embryonic development. Quantitative assays, such as microarrays and RNA sequencing, provide gene expression levels for a large number of genes, but do not contain spatial information. In contrast, in situ methods, such as in situ hybridization and immunohistochemistry, provide spatial resolution, but poor quantification and can only reveal the expression of one, or very few genes at a time. Furthermore, the usual methods of documenting the results, by photographing whole mounts or sections, makes it very difficult to assess the three-dimensional (3D) relationships between expressing and nonexpressing cells. Optical projection tomography (OPT) can capture the full 3D expression pattern in a whole embryo at a reasonable level of resolution and at moderately high throughput. A large database containing spatio-temporal patterns of expression for the mouse (e-Mouse Atlas Project, EMAP, www.emouseatlas.org) has been created, incorporating 3D information. Like the mouse, the chick is an important model in developmental biology and translational studies. To facilitate comparisons between these important model organisms, we have created a 3D anatomical atlas, accompanied by an anatomical ontology of the chick embryo and a database of gene expression patterns during chick development. This database is publicly available (www.echickatlas.org).
