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Expression Quantitative Trait Loci (eQTL) Analysis in Cancer.

Yaoming Liu1,2, Youqiong Ye2, Jing Gong3

  • 1State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, P. R. China.

Methods in Molecular Biology (Clifton, N.J.)
|December 19, 2019
PubMed
Summary
This summary is machine-generated.

This study presents a workflow for identifying expression quantitative trait loci (eQTLs) in cancer. Analyzing eQTLs in tumors helps understand genetic contributions to cancer development.

Keywords:
CancerCovariatesExpression quantitative trait lociGene expressionGenotypeMatrix eQTL

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Area of Science:

  • Genomics
  • Cancer Biology
  • Bioinformatics

Background:

  • Genetic variations influence gene expression, impacting complex traits and diseases.
  • Expression quantitative trait loci (eQTL) analysis connects genetic variations to gene expression levels.
  • Understanding eQTLs in tumors is crucial for elucidating tumorigenesis and development.

Purpose of the Study:

  • To describe a detailed workflow for identifying cis- and trans-eQTLs in cancer samples.
  • To provide a method for linking genetic variation to gene expression in the context of cancer.
  • To offer an intermediate phenotype for studying the role of risk alleles in tumorigenesis.

Main Methods:

  • Utilized existing bioinformatics packages and software for eQTL analysis.
  • Employed the Matrix eQTL package as a key component of the workflow.
  • Required input data including genotypes, gene expression levels, and covariates.

Main Results:

  • A reproducible workflow for identifying eQTLs in cancer was established.
  • The workflow facilitates the analysis of both cis- and trans-eQTLs in tumor samples.
  • Demonstrated the utility of eQTL analysis as an intermediate phenotype.

Conclusions:

  • The described workflow provides a robust method for eQTL identification in cancer research.
  • This approach enhances the understanding of how genetic variations contribute to cancer development.
  • The pipeline is adaptable for related research fields, promoting broader application.