Integration of Machine Learning Methods to Dissect Genetically Imputed Transcriptomic Profiles in Alzheimer’s Disease

Integration of Machine Learning Methods to Dissect Genetically Imputed Transcriptomic Profiles in Alzheimer’s Disease

The genetic component of many common traits is associated with the gene expression and several variants act as expression quantitative loci, regulating the gene expression in a tissue specific manner. In this work, we applied tissue-specific cis-eQTL gene expression prediction models on the genotype...

Full description

Bibliographic Details
Main Authors: Carlo Maj, Tiago Azevedo, Valentina Giansanti, Oleg Borisov, Giovanna Maria Dimitri, Simeon Spasov, Alzheimer’s Disease Neuroimaging Initiative, Pietro Lió, Ivan Merelli
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-09-01
Series:Frontiers in Genetics
Subjects:
eQTL
gene expression imputation
GTEx
variational autoencoder
support vector machine
deep learning
Online Access:https://www.frontiersin.org/article/10.3389/fgene.2019.00726/full

Internet

https://www.frontiersin.org/article/10.3389/fgene.2019.00726/full

Similar Items