Mixed Linear Model Approaches of Association Mapping for Complex Traits Based on Omics Variants

@article{Zhang2015MixedLM,
  title={Mixed Linear Model Approaches of Association Mapping for Complex Traits Based on Omics Variants},
  author={Fu-Tao Zhang and Zhihong Zhu and Xiaoran Tong and Zhi-Xiang Zhu and Ting Qi and Jun Zhu},
  journal={Scientific Reports},
  year={2015},
  volume={5}
}
Precise prediction for genetic architecture of complex traits is impeded by the limited understanding on genetic effects of complex traits, especially on gene-by-gene (GxG) and gene-by-environment (GxE) interaction. In the past decades, an explosion of high throughput technologies enables omics studies at multiple levels (such as genomics, transcriptomics, proteomics, and metabolomics). The analyses of large omics data, especially two-loci interaction analysis, are very time intensive… 
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References

SHOWING 1-10 OF 60 REFERENCES
Mapping the genetic architecture of complex traits in experimental populations
TLDR
A full-QTL model is presented with which to explore the genetic architecture of complex trait in multiple environments, which includes the effects of multiple QTLs, epistasis, QTL- by-environment interactions and epistasis-by- Environment interactions.
Epistasis analysis for quantitative traits by functional regression model.
TLDR
This work takes a genome region as a basic unit of interaction analysis and uses high-dimensional data reduction and functional data analysis techniques to develop a novel functional regression model to collectively test interactions between all possible pairs of single nucleotide polymorphisms within two genome regions.
An integrative genomics approach to infer causal associations between gene expression and disease
TLDR
It is shown that this approach can predict transcriptional responses to single gene–perturbation experiments using gene-expression data in the context of a segregating mouse population and the utility of this approach is demonstrated by identifying and experimentally validating the involvement of three new genes in susceptibility to obesity.
Meta‐analysis of gene‐environment interaction: joint estimation of SNP and SNP × environment regression coefficients
TLDR
A method of joint meta‐analysis (JMA) of SNP and SNP by Environment (SNP × E) regression coefficients for use in gene‐environment interaction studies and demonstrates that the JMA performs better than the others when both main and interaction effects are present.
Varying coefficient model for gene-environment interaction: a non-linear look
TLDR
The proposed method provides a powerful and testable framework for assessing non- linear G×E interaction under a varying coefficient model framework and allows one to assess the non-linear penetrance of a genetic variant under different environmental stimuli.
Development of GMDR-GPU for Gene-Gene Interaction Analysis and Its Application to WTCCC GWAS Data for Type 2 Diabetes
TLDR
A graphics processing unit (GPU)-based GMDR program is developed, able not only to analyze GWAS data but also to run much faster than the earlier version of theGMDR program, providing an independent replication of previously reported SNPs.
Mapping QTLs with epistatic effects and QTL×environment interactions by mixed linear model approaches
TLDR
A new methodology based on mixed linear models for mapping QTLs with digenic epistasis and QTL×environment (QE) interactions indicated that the mixed-model approaches could provide unbiased estimates for both positions and effects ofQTLs, as well as unbiased predicted values for QE interactions.
Incorporating Gene-Environment Interaction in Testing for Association with Rare Genetic Variants
TLDR
This work proposes interaction and joint tests for testing gene-environment interaction of rare genetic variants, a generalization of existing gene- Environment interaction tests for multiple genetic variants under certain conditions that can be applied to both binary and continuous traits.
...
1
2
3
4
5
...