scholarly journals Bayesian model selection in complex linear systems, as illustrated in genetic association studies

Biometrics ◽  
2013 ◽  
Vol 70 (1) ◽  
pp. 73-83 ◽  
Author(s):  
Xiaoquan Wen
Keyword(s):  
Model Selection ◽  
Linear Systems ◽  
Genetic Association ◽  
Bayesian Model ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Bayesian Model Selection ◽  
Complex Linear

scholarly journals Bayesian model selection for multiple QTLs mapping combining linkage disequilibrium and linkage

2014 ◽  
Vol 96 ◽  
Author(s):  
DAN JIANG ◽  
GUODA MA ◽  
RUNQING YANG ◽  
KESHEN LI ◽  
MING FANG
Keyword(s):  
Linkage Disequilibrium ◽  
Model Selection ◽  
Fine Mapping ◽  
Bayesian Model ◽  
Association Studies ◽  
Bayesian Model Selection ◽  
Small Region ◽  
Single Marker ◽  
Linkage Information ◽  
Haplotype Information

SummaryLinkage disequilibrium (LD) mapping is able to localize quantitative trait loci (QTL) within a rather small region (e.g. 2 cM), which is much narrower than linkage analysis (LA, usually 20 cM). The multilocus LD method utilizes haplotype information around putative mutation and takes historical recombination events into account, and thus provides a powerful method for further fine mapping. However, sometimes there are more than one QTLs in the region being studied. In this study, the Bayesian model selection implemented via the Markov chain Monte Carlo (MCMC) method is developed for fine mapping of multiple QTLs using haplotype information in a small region. The method combines LD as well as linkage information. A series of simulation experiments were conducted to investigate the behavior of the method. The results showed that this new multiple QTLs method was more efficient in separating closely linked QTLs than single-marker association studies.

scholarly journals Fine scale human genetic structure in three regions of Cameroon reveals episodic diversifying selection

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kevin K. Esoh ◽  
Tobias O. Apinjoh ◽  
Steven G. Nyanjom ◽  
Ambroise Wonkam ◽  
Emile R. Chimusa ◽  
...  
Keyword(s):  
Genetic Structure ◽  
Ethnic Groups ◽  
Genetic Association ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Genomic Region ◽  
Sub Saharan Africa ◽  
Genome Wide Association Studies ◽  
Fine Scale ◽  
Sub Saharan

AbstractInferences from genetic association studies rely largely on the definition and description of the underlying populations that highlight their genetic similarities and differences. The clustering of human populations into subgroups (population structure) can significantly confound disease associations. This study investigated the fine-scale genetic structure within Cameroon that may underlie disparities observed with Cameroonian ethnicities in malaria genome-wide association studies in sub-Saharan Africa. Genotype data of 1073 individuals from three regions and three ethnic groups in Cameroon were analyzed using measures of genetic proximity to ascertain fine-scale genetic structure. Model-based clustering revealed distinct ancestral proportions among the Bantu, Semi-Bantu and Foulbe ethnic groups, while haplotype-based coancestry estimation revealed possible longstanding and ongoing sympatric differentiation among individuals of the Foulbe ethnic group, and their Bantu and Semi-Bantu counterparts. A genome scan found strong selection signatures in the HLA gene region, confirming longstanding knowledge of natural selection on this genomic region in African populations following immense disease pressure. Signatures of selection were also observed in the HBB gene cluster, a genomic region known to be under strong balancing selection in sub-Saharan Africa due to its co-evolution with malaria. This study further supports the role of evolution in shaping genomes of Cameroonian populations and reveals fine-scale hierarchical structure among and within Cameroonian ethnicities that may impact genetic association studies in the country.

scholarly journals Bayesian model selection on scalar ε -field dark energy

2021 ◽  
Vol 103 (4) ◽  
Author(s):  
J. Alberto Vázquez ◽  
David Tamayo ◽  
Anjan A. Sen ◽  
Israel Quiros
Keyword(s):  
Dark Energy ◽  
Model Selection ◽  
Bayesian Model ◽  
Bayesian Model Selection

scholarly journals Evaluation of genome-wide power of genetic association studies based on empirical data from the HapMap project

2007 ◽  
Vol 16 (20) ◽  
pp. 2494-2505 ◽  
Author(s):  
Yasuhito Nannya ◽  
Kenjiro Taura ◽  
Mineo Kurokawa ◽  
Shigeru Chiba ◽  
Seishi Ogawa
Keyword(s):  
Genetic Association ◽  
Empirical Data ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Hapmap Project ◽  
Genome Wide
Sign in / Sign up

Export Citation Format

Share Document