title: Shape mapping: genetic mapping meets geometric morphometrics.
abstract: Knowledge about biological shape has important implications in biology and biomedicine, but the underlying genetic mechanisms for shape variation have not been well studied. Statistical models play a pivotal role in mapping specific quantitative trait loci (QTLs) that contribute to biological shape and its developmental trajectories. We describe and assess a statistical framework for shape gene identification that incorporates shape and image analysis into a mixture-model framework for QTL mapping. Statistical parameters that define genotype-specific differences in biological shape are estimated by implementing statistical and computational algorithms. A state-of-the-art procedure is described to examine the control patterns of specific QTLs on the origin, properties and functions of biological shape. The statistical framework described will help to address many integrative biological and genetic questions and challenges in shape variation faced by the life sciences community.
authors: Wenhao
authors: W
authors: Bo
authors: Zhong
authors: Z
authors: Wang
authors: Fang
authors: F
authors: Xu
authors: Guifang
authors: G
authors: Fu
authors: Yihan
authors: Y
authors: Sui
authors: Weimiao
authors: W
authors: Wu
authors: Xuli
authors: X
authors: Zhu
authors: Danni
authors: D
authors: Yin
authors: Qin
authors: Q
authors: Yan
authors: Rongling
authors: R
authors: Wu
mesh_terms: D000465:Algorithms; D015233:Models, Statistical; D040641:Quantitative Trait Loci