Testing the accuracy of 3D automatic landmarking via genome-wide association studies

Author:

Savriama YolandORCID,Tautz DiethardORCID

Abstract

AbstractBackgroundVarious advances in 3D automatic phenotyping and particularly in landmark-based geometric morphometric methods have been made, but only a few studies have tested the reliability of such automatic procedures in morphometric analyses. It is generally accepted that automatic landmarking compromises the capture of the actual biological variation, and this not only affects its performance to effectively detect differences among sample means but also the structure of covariance matrices. However, no studies have directly tested the actual impact of such landmarking approaches in analyses requiring a large number of specimens and for which the precision of phenotyping is crucial to capture an actual biological signal adequately.ResultsHere, we use a recently developed 3D atlas-based automatic landmarking method to test its accuracy in detecting QTLs associated with craniofacial development of the house mouse skull and lower jaws for a large number of specimens (circa 700) that were previously phenotyped via a semiautomatic landmarking method complemented with manual adjustment. We compare both landmarking methods with univariate and multivariate mapping of the skull and the lower jaws. In the univariate mapping, the automatic approach failed to recover the same SNPs and found only 1 out of 17 previously identified QTLs for the skull, but found one new QTL. Similarly, for the lower jaws, the automatic approach failed to recover the same SNPs but found 2 neighbouring SNPs for 1 out of 8 previously identified QTLs. For centroid size, the same general results were recovered by the automatic method for both the skull and lower jaws, with the same peak SNP being found for the lower jaws. In the multivariate mapping, the automatic approach did not detect the same markers nor QTLs having their regions overlapping with the ones identified with the semi-automatic procedure for the skull, while the same marker, which is also the peak SNP and sole QTL, was recovered by the automatic pipeline for lower jaws.ConclusionOur results confirm the notion that information is lost in the automated landmarking procedure but somewhat dependent on the analyzed structure. The automatic method seems to capture certain types of structures slightly better, such as lower jaws whose shape is almost entirely summarized by its outline and could be assimilated as a 2D flat object. By contrast, the more apparent 3D features exhibited by a structure such as the skull are not adequately captured by the automatic method. We conclude that using 3D atlas-based automatic landmarking methods requires careful consideration of the experimental question and the cautious interpretation of their results.

Publisher

Cold Spring Harbor Laboratory

Reference48 articles.

1. geomorph: an R package for the collection and analysis of geometric morphometric shape data;Methods in Ecology and Evolution,2013

2. Anand, L. , 2019 chromoMap: an R package for interactive visualization and annotation of chromosomes. bioRxiv:605600.

3. Avants, B.B. , B.M. Kandel , J.T. Duda , P.A. Cook , and N.J. Tustison , 2015 AntsR: An R package providing ANTs features in R. Available at https://github.com/ANTsX/ANTsR (accessed 15 October 2020).

4. Advanced normalization tools (ANTS);Insight j,2009

5. A reproducible evaluation of ANTs similarity metric performance in brain image registration

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3