Connecting mathematical models to genomes: joint estimation of model parameters and genome-wide marker effects on these parameters | Zendy

Akio Onogi | Zendy

Open Access

Connecting mathematical models to genomes: joint estimation of model parameters and genome-wide marker effects on these parameters

Author(s) -

Akio Onogi

Publication year - 2020

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa129

Subject(s) - computer science , scripting language , r package , estimation , statistical model , data mining , genome , genome wide association study , computational biology , genetic architecture , machine learning , biology , quantitative trait locus , genotype , genetics , computational science , management , single nucleotide polymorphism , economics , gene , operating system

Parameters of mathematical models used in biology may be genotype-specific and regarded as new traits. Therefore, an accurate estimation of these parameters and the association mapping on the estimated parameters can lead to important findings regarding the genetic architecture of biological processes. In this study, a statistical framework for a joint analysis (JA) of model parameters and genome-wide marker effects on these parameters was proposed and evaluated.

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