Bivariate causal mixture model quantifies polygenic overlap between complex traits beyond genetic correlation
To better understand the phenotypic relationships of complex traits it is also important to understand their genetic overlap. Here, Frei et al. develop MiXeR which uses GWAS summary statistics to evaluate the polygenic overlap between two traits irrespective of their genetic correlation.
Guardado en:
Autores principales: | Oleksandr Frei, Dominic Holland, Olav B. Smeland, Alexey A. Shadrin, Chun Chieh Fan, Steffen Maeland, Kevin S. O’Connell, Yunpeng Wang, Srdjan Djurovic, Wesley K. Thompson, Ole A. Andreassen, Anders M. Dale |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2019
|
Materias: | |
Acceso en línea: | https://doaj.org/article/e81f038c77814a4e89212eabbff80ce4 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
The genetic architecture of the human thalamus and its overlap with ten common brain disorders
por: Torbjørn Elvsåshagen, et al.
Publicado: (2021) -
Author Correction: Understanding the genetic determinants of the brain with MOSTest
por: Dennis van der Meer, et al.
Publicado: (2020) -
Understanding the genetic determinants of the brain with MOSTest
por: Dennis van der Meer, et al.
Publicado: (2020) -
Identification of genetic loci shared between schizophrenia and the Big Five personality traits
por: Olav B. Smeland, et al.
Publicado: (2017) -
Fast and effective pseudo transfer entropy for bivariate data-driven causal inference
por: Riccardo Silini, et al.
Publicado: (2021)