A bioimage informatics platform for high-throughput embryo phenotyping

James M Brown, Neil R Horner, Thomas N Lawson, Tanja Fiegel, Simon Greenaway, Hugh Morgan, Natalie Ring, Luis Santos, Duncan Sneddon, Lydia Teboul, Jennifer Vibert, Gagarine Yaikhom, Henrik Westerberg, Ann-Marie Mallon

Research output: Contribution to journalArticle

3 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)41-51
Number of pages11
JournalBriefings in Bioinformatics
Volume19
Issue number1
Early online date14 Oct 2016
DOIs
Publication statusPublished - 1 Jan 2018

Keywords

  • Automated analysis
  • Bioimage informatics
  • Embryonic phenotyping
  • High-throughput
  • Image processing
  • Software tools

ASJC Scopus subject areas

  • Information Systems
  • Molecular Biology

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