Determining Genetic Causal Variants Through Multivariate Regression Using Mixture Model Penalty

Autor: V. S. Sundar, Chun-Chieh Fan, Dominic Holland, Anders M. Dale
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: Frontiers in Genetics, Vol 9 (2018)
Druh dokumentu: article
ISSN: 1664-8021
DOI: 10.3389/fgene.2018.00077
Popis: With the availability of high-throughput sequencing data, identification of genetic causal variants accurately requires the efficient incorporation of function annotation data into the optimization routine. This motivates the need for development of novel methods for genome wide association studies with special focus on fine-mapping capabilities. A penalty function method that is simple to implement and capable of integrating functional annotation information into the estimation procedure, is proposed in this work. The idea is to use the prior distribution of the effect sizes explicitly as a penalty function. The estimates obtained are shown to be better correlated with the true effect sizes (in comparison with a few existing techniques). An increase in the positive and negative predictive value is demonstrated using Hapgen2 simulated data.
Databáze: Directory of Open Access Journals