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ReQTL: identifying correlations between expressed SNVs and gene expression using RNA-sequencing data

机译:REQTL:使用RNA测序数据识别表达的SNV和基因表达之间的相关性

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摘要

Motivation: By testing for associations between DNA genotypes and gene expression levels, expression quantitative trait locus (eQTL) analyses have been instrumental in understanding how thousands of single nucleotide variants (SNVs) may affect gene expression. As compared to DNA genotypes, RNA genetic variation represents a phenotypic trait that reflects the actual allele content of the studied system. RNA genetic variation at expressed SNV loci can be estimated using the proportion of alleles bearing the variant nucleotide (variant allele fraction, VAF(RNA)). VAF(RNA) is a continuous measure which allows for precise allele quantitation in loci where the RNA alleles do not scale with the genotype count. We describe a method to correlate VAF(RNA) with gene expression and assess its ability to identify genetically regulated expression solely from RNA-sequencing (RNA-seq) datasets.
机译:动机:通过测试DNA基因型和基因表达水平之间的关联,表达定量性状基因座(EQT1)分析已经有助于理解成千上万的单核苷酸变体(SNV)可能影响基因表达。 与DNA基因型相比,RNA遗传变异代表了反映了研究系统的实际等位基因含量的表型特征。 表达的SNV基因座的RNA遗传变异可以使用承载变体核苷酸的等位基因的比例来估计(变体等位基因级分,VAF(RNA))。 VAF(RNA)是一种连续度量,允许在基因座中进行精确的等位基因定量,其中RNA等位基因不会与基因型计数扩展。 我们描述了一种将VAF(RNA)与基因表达相关的方法,并评估其仅从RNA测序(RNA-SEQ)数据集识别遗传调节表达的能力。

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  • 来源
    《Bioinformatics》 |2020年第5期|共9页
  • 作者单位

    Dana Farber Canc Inst Dept Med Oncol Boston MA 02215 USA;

    George Washington Univ McCormick Genom &

    Prote Ctr Biochem &

    Mol Med Washington DC 20037 USA;

    George Washington Univ McCormick Genom &

    Prote Ctr Biochem &

    Mol Med Washington DC 20037 USA;

    George Washington Univ Sch Med &

    Hlth Sci Comp Applicat Support Serv Washington DC 20037 USA;

    George Washington Univ McCormick Genom &

    Prote Ctr Biochem &

    Mol Med Washington DC 20037 USA;

    George Washington Univ McCormick Genom &

    Prote Ctr Biochem &

    Mol Med Washington DC 20037 USA;

    Univ Exeter Dept Math Exeter EX4 4QD Devon England;

    George Washington Univ McCormick Genom &

    Prote Ctr Biochem &

    Mol Med Washington DC 20037 USA;

    George Washington Univ Sch Med &

    Hlth Sci Dept Biochem &

    Mol Med Washington DC 20037 USA;

    George Washington Univ McCormick Genom &

    Prote Ctr Biochem &

    Mol Med Washington DC 20037 USA;

    George Washington Univ McCormick Genom &

    Prote Ctr Biochem &

    Mol Med Washington DC 20037 USA;

    George Washington Univ Computat Biol Inst Dept Biostat &

    Bioinformat Milken Inst Sch Publ Hlth Washington DC 20052 USA;

    Univ Exeter Dept Math Exeter EX4 4QD Devon England;

    George Washington Univ McCormick Genom &

    Prote Ctr Biochem &

    Mol Med Washington DC 20037 USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 生物工程学(生物技术);
  • 关键词

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