文章基本信息

标题：MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses
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作者：Jay Devine ; MartaVidal-García ; Wei Liu 等
期刊名称：Scientific Data
电子版ISSN：2052-4463
出版年度：2022
卷号：9
期号：1
页码：1-18
DOI：10.1038/s41597-022-01338-x
语种：English
出版社：Nature Publishing Group
摘要：Complex morphological traits are the product of many genes with transient or lasting developmental efects that interact in anatomical context . Mouse models are a key resource for disentangling such efects, because they ofer myriad tools for manipulating the genome in a controlled environment . Unfortunately, phenotypic data are often obtained using laboratory-specifc protocols, resulting in self-contained datasets that are difcult to relate to one another for larger scale analyses . To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10 .5, E11 .5, E14 .5, E15 .5, E18 .5, and adulthood . To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics . Alongside stage-specifc atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056) . Our workfow is open-source to encourage transparency and reproducible data collection . The MusMorph data and scripts are available on FaceBase (www.facebase.org, https://doi.org/10.25550/3-HXMC) and GitHub (https://github.com/jaydevine/MusMorph) .