TY - JOUR
T1 - A statistical model for mapping morphological shape
AU - Fu, Guifang
AU - Berg, Arthur
AU - Das, Kiranmoy
AU - Li, Jiahan
AU - Li, Runze
AU - Wu, Rongling
N1 - Funding Information:
NSF/NIH Joint grant DMS/NIGMS-0540745 and the Changjiang Scholars Award to RW. RL’s research is supported by NIDA, NIH grants R21 DA024260 and R21 DA024266. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIDA or the NIH.
PY - 2010
Y1 - 2010
N2 - Background. Living things come in all shapes and sizes, from bacteria, plants, and animals to humans. Knowledge about the genetic mechanisms for biological shape has far-reaching implications for a range spectrum of scientific disciplines including anthropology, agriculture, developmental biology, evolution and biomedicine. Results. We derived a statistical model for mapping specific genes or quantitative trait loci (QTLs) that control morphological shape. The model was formulated within the mixture framework, in which different types of shape are thought to result from genotypic discrepancies at a QTL. The EM algorithm was implemented to estimate QTL genotype-specific shapes based on a shape correspondence analysis. Computer simulation was used to investigate the statistical property of the model. Conclusion. By identifying specific QTLs for morphological shape, the model developed will help to ask, disseminate and address many major integrative biological and genetic questions and challenges in the genetic control of biological shape and function.
AB - Background. Living things come in all shapes and sizes, from bacteria, plants, and animals to humans. Knowledge about the genetic mechanisms for biological shape has far-reaching implications for a range spectrum of scientific disciplines including anthropology, agriculture, developmental biology, evolution and biomedicine. Results. We derived a statistical model for mapping specific genes or quantitative trait loci (QTLs) that control morphological shape. The model was formulated within the mixture framework, in which different types of shape are thought to result from genotypic discrepancies at a QTL. The EM algorithm was implemented to estimate QTL genotype-specific shapes based on a shape correspondence analysis. Computer simulation was used to investigate the statistical property of the model. Conclusion. By identifying specific QTLs for morphological shape, the model developed will help to ask, disseminate and address many major integrative biological and genetic questions and challenges in the genetic control of biological shape and function.
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U2 - 10.1186/1742-4682-7-28
DO - 10.1186/1742-4682-7-28
M3 - Article
C2 - 20594352
AN - SCOPUS:77954040136
SN - 1742-4682
VL - 7
JO - Theoretical Biology and Medical Modelling
JF - Theoretical Biology and Medical Modelling
IS - 1
M1 - 28
ER -