A bioimage informatics platform for high-throughput embryo phenotyping

Brown, James and Horner, Neil R and Lawson, Thomas N and Fiegel, Tanja and Greenaway, Simon and Morgan, Hugh and Ring, Natalie and Santos, Luis and Sneddon, Duncan and Teboul, Lydia and Vibert, Jennifer and Yaikhom, Gagarine and Westerberg, Henrik and Mallon, Ann-Marie (2018) A bioimage informatics platform for high-throughput embryo phenotyping. Briefings in Bioinformatics, 19 (1). pp. 41-51. ISSN 1467-5463

Full content URL: https://doi.org/10.1093/bib/bbw101

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A bioimage informatics platform for high-throughput embryo phenotyping
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Abstract

High-throughput phenotyping is a cornerstone of numerous functional genomics projects. In recent years, imaging screens have become increasingly important in understanding gene–phenotype relationships in studies of cells, tissues and whole organisms. Three-dimensional (3D) imaging has risen to prominence in the field of developmental biology for its ability to capture whole embryo morphology and gene expression, as exemplified by the International Mouse Phenotyping Consortium (IMPC). Large volumes of image data are being acquired by multiple institutions around the world that encompass a range of modalities, proprietary software and metadata. To facilitate robust downstream analysis, images and metadata must be standardized to account for these differences. As an open scientific enterprise, making the data readily accessible is essential so that members of biomedical and clinical research communities can study the images for themselves without the need for highly specialized software or technical expertise. In this article, we present a platform of software tools that facilitate the upload, analysis and dissemination of 3D images for the IMPC. Over 750 reconstructions from 80 embryonic lethal and subviable lines have been captured to date, all of which are openly accessible at mousephenotype.org. Although designed for the IMPC, all software is available under an open-source licence for others to use and develop further. Ongoing developments aim to increase throughput and improve the analysis and dissemination of image data. Furthermore, we aim to ensure that images are searchable so that users can locate relevant images associated with genes, phenotypes or human diseases of interest.

Keywords:bioimage informatics, image processing, embryonic phenotyping, automated analysis, high-throughput, software tools
Subjects:G Mathematical and Computer Sciences > G740 Computer Vision
C Biological Sciences > C400 Genetics
Divisions:College of Science > School of Computer Science
ID Code:35643
Deposited On:15 Apr 2019 08:46

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