1. LAMA: automated image analysis for the developmental phenotyping of mouse embryos
- Author
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Lydia Teboul, James M. Brown, Neil R. Horner, Shanmugasundaram Venkataraman, Steve D.M. Brown, Henrik Westerberg, Ramón Casero, Ann-Marie Mallon, Matthijs C. van Eede, Sara Wells, Michael D. Wong, Sara Johnson, R. Mark Henkelman, and Chris Armit
- Subjects
G740 Computer Vision ,Automated ,Micro-CT ,Mouse ,Computational biology ,Biology ,Imaging data ,Imaging modalities ,03 medical and health sciences ,Mice ,0302 clinical medicine ,Techniques and Resources ,Imaging, Three-Dimensional ,Control data ,Image Processing, Computer-Assisted ,Animals ,Statistical analysis ,Segmentation ,Molecular Biology ,C141 Developmental Biology ,030304 developmental biology ,Mice, Knockout ,0303 health sciences ,Computational ,Embryo ,G400 Computer Science ,Embryo, Mammalian ,Pipeline (software) ,Mice, Inbred C57BL ,ComputingMethodologies_PATTERNRECOGNITION ,Phenotype ,Phenotyping ,Sample number ,Female ,030217 neurology & neurosurgery ,Software ,Developmental Biology - Abstract
Advanced 3D imaging modalities, such as micro-computed tomography (micro-CT), have been incorporated into the high-throughput embryo pipeline of the International Mouse Phenotyping Consortium (IMPC). This project generates large volumes of raw data that cannot be immediately exploited without significant resources of personnel and expertise. Thus, rapid automated annotation is crucial to ensure that 3D imaging data can be integrated with other multi-dimensional phenotyping data. We present an automated computational mouse embryo phenotyping pipeline that harnesses the large amount of wild-type control data available in the IMPC embryo pipeline in order to address issues of low mutant sample number as well as incomplete penetrance and variable expressivity. We also investigate the effect of developmental substage on automated phenotyping results. Designed primarily for developmental biologists, our software performs image pre-processing, registration, statistical analysis and segmentation of embryo images. We also present a novel anatomical E14.5 embryo atlas average and, using it with LAMA, show that we can uncover known and novel dysmorphology from two IMPC knockout lines., Summary: Introducing an easy-to-use automated anatomical phenotyping pipeline for mouse embryos along with a highly-detailed anatomical E14.5 atlas.
- Published
- 2021