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Integration of Multi-omics Data for Expression Quantitative Trait Loci (eQTL) Analysis and eQTL Epistasis. | LitMetric

Integration of Multi-omics Data for Expression Quantitative Trait Loci (eQTL) Analysis and eQTL Epistasis.

Methods Mol Biol

Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, USA.

Published: December 2020

AI Article Synopsis

Article Abstract

Expression quantitative trait loci (eQTL) mapping studies identify genetic loci that regulate gene expression. eQTL mapping studies can capture gene regulatory interactions and provide insight into the genetic mechanism of biological systems. Recently, the integration of multi-omics data, such as single-nucleotide polymorphisms (SNPs), copy number variations (CNVs), DNA methylation, and gene expression, plays an important role in elucidating complex biological systems, since biological systems involve a sequence of complex interactions between various biological processes. This chapter introduces multi-omics data that have been used in many eQTL studies and integrative methodologies that incorporate multi-omics data for eQTL studies. Furthermore, we describe a statistical approach that can detect nonlinear causal relationships between eQTLs, called eQTL epistasis, and its importance.

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http://dx.doi.org/10.1007/978-1-0716-0026-9_11DOI Listing

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