Allelic mapping bias in RNA-sequencing is not a major confounder in eQTL studies.
Allelic mapping bias in RNA-sequencing is not a major confounder in eQTL studies.
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RNA测序中的等位基因映射偏差不是EQTL研究中的主要混杂因素。
DOI：
10.1186/s13059-014-0467-2
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发表时间：
2014-09-20
期刊：
影响因子：
12.3
通讯作者：
Lappalainen T
中科院分区：
文献类型：
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作者：
Panousis NI;Gutierrez-Arcelus M;Dermitzakis ET;Lappalainen T
RNA测序（RNA-Seq）是定量表达定量性状基因座（EQTL）的基因表达的当前金标准方法，但是，这些研究的潜在警告是RNA-seq读取携带非参考等位基因的变体等位基因基因座的可能性较低，可以正确地映射到参考基因组，这可能会偏向基因量并引起假阳性EQTL关联。 EQTL发现中的Allic映射偏差。
我们模拟RNA-seq读取9.5 m公共SNP和Indels的映射，其中15.6％的变体显示了参考的偏差映射率与非参考读数，但是，从185个个人的EQTL数据集中删除了潜在的偏见RNA-seq读取。对基因和外显子量化和EQTL的影响非常小。高映射偏见。
我们的结果表明，RNA-seq量化通常是鲁棒性的，对shiric映射偏差，这对EQTL的发现没有严重影响，我们仍然提供了预定的偏见局部目录，以更好地控制映射偏见以获得更准确的偏见以获得更准确的偏见。导致未来的RNA-seq研究。
本文的在线版本（DOI：10.1186/S13059-014-0467-2）包含补充材料，可供授权用户使用。
RNA sequencing (RNA-seq) is the current gold-standard method to quantify gene expression for expression quantitative trait locus (eQTL) studies. However, a potential caveat in these studies is that RNA-seq reads carrying the non-reference allele of variant loci can have lower probability to map correctly to the reference genome, which could bias gene quantifications and cause false positive eQTL associations. In this study, we analyze the effect of this allelic mapping bias in eQTL discovery. We simulate RNA-seq read mapping over 9.5 M common SNPs and indels, with 15.6% of variants showing biased mapping rate for reference versus non-reference reads. However, removing potentially biased RNA-seq reads from an eQTL dataset of 185 individuals has a very small effect on gene and exon quantifications and eQTL discovery. We detect only a handful of likely false positive eQTLs, and overall eQTL SNPs show no significant enrichment for high mapping bias. Our results suggest that RNA-seq quantifications are generally robust against allelic mapping bias, and that this does not have a severe effect on eQTL discovery. Nevertheless, we provide our catalog of putatively biased loci to allow better controlling for mapping bias to obtain more accurate results in future RNA-seq studies. The online version of this article (doi:10.1186/s13059-014-0467-2) contains supplementary material, which is available to authorized users.
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来自1,092个人基因组的遗传变异的综合图。
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影响因子：
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