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An independent component analysis confounding factor correction framework for identifying broad impact expression

Jin Hyun Ju1,2, Sushila A Shenoy1, Ronald G Crystal1

  • 1Department of Genetic Medicine, Weill Cornell Medical College, New York, NY, United States of America.

Plos Computational Biology
|May 16, 2017
PubMed
Summary

We developed CONFETI, a new method using Independent Component Analysis (ICA) to identify broad impact expression Quantitative Trait Loci (eQTL) while accounting for confounding factors. CONFETI improves eQTL detection and replication across multiple human datasets.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Systems Biology

Background:

  • Genome-wide expression Quantitative Trait Loci (eQTL) studies are crucial for understanding gene expression and complex diseases.
  • Broad impact eQTL, affecting multiple genes, are valuable for network modeling but challenging to identify due to confounding factors.

Purpose of the Study:

  • To introduce CONFETI (Confounding Factor Estimation Through Independent component analysis), a novel framework for identifying broad impact eQTL.
  • To address the challenge of distinguishing true broad impact eQTL from non-genetic confounding factors.

Main Methods:

  • Employed Independent Component Analysis (ICA) within a mixed model framework to identify genetic variation potentially from broad impact eQTL.
  • Evaluated CONFETI's performance on synthetic data and its ability to replicate eQTL across human datasets (MuTHER, DGN, NESDA, GTEx).

Main Results:

  • CONFETI demonstrated superior performance in recovering broad impact eQTL from synthetic data compared to existing methods.
  • CONFETI identified and replicated cis- and trans-eQTL across multiple human cohorts, showing comparable or better performance than other confounding factor methods.
  • A limited number of broad impact eQTL were identified and replicated, even with CONFETI.

Conclusions:

  • CONFETI is an effective tool for identifying broad impact eQTL and controlling for confounding factors in human expression data.
  • The identification of broad impact eQTL remains challenging, necessitating caution in biological interpretations of previously reported findings.