Cargando…

OSCA: a tool for omic-data-based complex trait analysis

The rapid increase of omic data has greatly facilitated the investigation of associations between omic profiles such as DNA methylation (DNAm) and complex traits in large cohorts. Here, we propose a mixed-linear-model-based method called MOMENT that tests for association between a DNAm probe and tra...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Futao, Chen, Wenhan, Zhu, Zhihong, Zhang, Qian, Nabais, Marta F., Qi, Ting, Deary, Ian J., Wray, Naomi R., Visscher, Peter M., McRae, Allan F., Yang, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6537380/
https://www.ncbi.nlm.nih.gov/pubmed/31138268
http://dx.doi.org/10.1186/s13059-019-1718-z
Descripción
Sumario:The rapid increase of omic data has greatly facilitated the investigation of associations between omic profiles such as DNA methylation (DNAm) and complex traits in large cohorts. Here, we propose a mixed-linear-model-based method called MOMENT that tests for association between a DNAm probe and trait with all other distal probes fitted in multiple random-effect components to account for unobserved confounders. We demonstrate by simulations that MOMENT shows a lower false positive rate and more robustness than existing methods. MOMENT has been implemented in a versatile software package called OSCA together with a number of other implementations for omic-data-based analyses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-019-1718-z) contains supplementary material, which is available to authorized users.