Nancy George - Single Cell Expression Atlas and FlyBase - the Fly Cell Atlas Anatomograms
Channel: Biocuration Conference 2023
Date: 2023-06-22

*Session:* April 26 - Community 1 - 03

*Abstract:* The Single Cell Expression Atlas knowledge base analyses curated, high quality gene expression data at the level of single cells. Data are then displayed through dimensionality reduction plots and heatmaps to show how cells cluster based on their expression profiles. However, in order to truly understand how expression profiles define cell populations and are altered by perturbations, expression profiles need to be linked to cell types and novel subpopulations identified. Thus, the single cell anatomogram project was born. Its aim is to display cell types realistically within their parent structures alongside cell types provided by the data submitter. Anatomograms are now available representing adult tissues for lung; placenta; kidney; pancreas and liver. The single cell anatomogram project is a diverse collaboration between scientific experts, curators, ontologists, artists, bioinformaticians and web developers to derive interactive images which show cells at single cell resolution within the wider context of the tissue. These images allow users to delve into lifelike representations of organ structures from macro-structures down to single cells within the tissue. Initially, artists work with curators and scientific experts, creating true to life shapes from real data, such as immunohistochemistry and immunofluorescence images to create structures and cell types 'in situ'. Cell shapes and detailed structures are layered on top of the tissue structure like a cake. Each shape is mapped either to an existing ontology term or a new term and relationships are created, in collaboration with ontologists from UBERON and Cell Ontology. This allows us to recreate the existing biological hierarchy from structure to cell type e.g. kidney - nephron - loop of Henle - epithelial cell of loop of Henle. Once illustrations have been created, mapped to their ontology identifiers and the appropriate hierarchy defined, these constructs are then incorporated into the Single Cell Expression Atlas by our web development team. Developers ensure that the resulting images are interactive and users can select regions within a tissue to ‘zoom into’ down to the level of individual cells within sub-structures of that tissue. This is enabled by the standardised bioinformatics analysis pipelines that adequately merge data with curated metadata. Last, but not least, is the data and cell types inferred from expression profiles. Author-defined inferred cell types are mapped where possible to ontology terms allowing us to identify the same cell types across multiple datasets. Once a user lands on these datasets, the anatomograms are displayed alongside a heatmap showing the top 5 genes per cell type associated with that dataset. When a cell type ‘shape’ is selected this then lights up showing that population, giving context to the data. Thus anatomograms provide a new perspective on visualisation of multi-layered biological information at the single cell level.