scholarly journals Bayesian model averaging for the X-chromosome inactivation dilemma in genetic association study

Biostatistics ◽  
2018 ◽  
Author(s):  
Bo Chen ◽  
Radu V Craiu ◽  
Lei Sun
Keyword(s):  
Association Study ◽  
Genetic Association ◽  
X Chromosome ◽  
Bayesian Model ◽  
Genetic Association Study ◽  
Bayesian Model Averaging ◽  
Model Averaging ◽  
X Chromosome Inactivation ◽  
Chromosome Inactivation

X-chromosome genetic association test incorporating X-chromosome inactivation and imprinting effects

2019 ◽  
Vol 98 (4) ◽  
Author(s):  
Wei Liu ◽  
Bei-Qi Wang ◽  
Guojun Liu-Fu ◽  
Wing Kam Fung ◽  
Ji-Yuan Zhou
Keyword(s):  
Genetic Association ◽  
X Chromosome ◽  
X Chromosome Inactivation ◽  
Association Test ◽  
Chromosome Inactivation ◽  
Genetic Association Test

Bayesian Model Averaging for Genetic Association Studies

2013 ◽  
pp. 208-223 ◽  
Author(s):  
Christine Peterson ◽  
Michael Swartz ◽  
Sanjay Shete ◽  
Marina Vannucci
Keyword(s):  
Genetic Association ◽  
Bayesian Model ◽  
Bayesian Model Averaging ◽  
Association Studies ◽  
Model Averaging ◽  
Genetic Association Studies

A novel model for the X-chromosome inactivation association on survival data

2019 ◽  
Vol 29 (5) ◽  
pp. 1305-1314
Author(s):  
Dongxiao Han ◽  
Meiling Hao ◽  
Lianqiang Qu ◽  
Wei Xu
Keyword(s):  
Genetic Association ◽  
X Chromosome ◽  
Survival Data ◽  
Biological Process ◽  
Random Effect ◽  
X Chromosome Inactivation ◽  
Chromosome Inactivation ◽  
Model Parameters ◽  
Censored Survival Data ◽  
Novel Model

The X-linked genetic association is overlooked in most of the genetic studies because of the complexity of X-chromosome inactivation process. In fact, the biological process of the gene at the same locus can vary across different subjects. Besides, the skewness of X-chromosome inactivation is inherently subject-specific (even tissue-specific within subjects) and cannot be accurately represented by a population-level parameter. To tackle this issue, a new model is proposed to incorporate the X-linked genetic association into right-censored survival data. The novel model can present that the X-linked genes on different subjects may go through different biological processes via a mixed distribution. Further, a random effect is employed to describe the uncertainty of the biological process for every subject. The proposed method can derive the probability for the escape of X-chromosome inactivation and derive the unbiased estimates of the model parameters. The Legendre–Gauss Quadrature method is used to approximate the integration over the random effect. Finite sample performance of this method is examined via extensive simulation studies. An application is illustrated with the implementation on a cancer genetic study with right-censored survival data.

Genetic association study in schizophrenia and intermediate phenotypes

2009 ◽  
Vol 42 (05) ◽  
Author(s):  
M Boxleitner ◽  
I Giegling ◽  
AM Hartmann ◽  
J Genius ◽  
A Ruppert ◽  
...  
Keyword(s):  
Association Study ◽  
Genetic Association ◽  
Genetic Association Study ◽  
Intermediate Phenotypes

X-linked CNV and skewed X-chromosome inactivation

2020 ◽  
pp. 19-21
Author(s):  
Е.А. Фонова ◽  
Е.Н. Толмачева ◽  
А.А. Кашеварова ◽  
М.Е. Лопаткина ◽  
К.А. Павлова ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Intellectual Disability ◽  
X Chromosome ◽  
Copy Number ◽  
Copy Number Variations ◽  
X Chromosome Inactivation ◽  
Chromosome Inactivation ◽  
Chromosome X ◽  
Skewed X Chromosome Inactivation

Смещение инактивации Х-хромосомы может быть следствием и маркером нарушения клеточной пролиферации при вариациях числа копий ДНК на Х-хромосоме. Х-сцепленные CNV выявляются как у женщин с невынашиванием беременности и смещением инактивации Х-хромосомы (с частотой 33,3%), так и у пациентов с умственной отсталостью и смещением инактивацией у их матерей (с частотой 40%). A skewed X-chromosome inactivation can be a consequence and a marker of impaired cell proliferation in the presence of copy number variations (CNV) on the X chromosome. X-linked CNVs are detected in women with miscarriages and a skewed X-chromosome inactivation (with a frequency of 33.3%), as well as in patients with intellectual disability and skewed X-chromosome inactivation in their mothers (with a frequency of 40%).

Selecting Predictors by Using Bayesian Model Averaging in Bridge Models

2012 ◽  
Author(s):  
Lorenzo Bencivelli ◽  
Massimiliano Giuseppe Marcellino ◽  
Gianluca Moretti
Keyword(s):  
Bayesian Model ◽  
Bayesian Model Averaging ◽  
Model Averaging ◽  
Bridge Models
Sign in / Sign up

Export Citation Format

Share Document