Cole Nolan, Wu William, Head S Taylor, Bresnahan Sean T, Bhattacharya Arjun
Department of Biostatistics, University of Washington, Seattle, WA, USA.
Department of BioSciences, Rice University, Houston, TX, USA.
bioRxiv. 2025 Aug 24:2025.08.20.671303. doi: 10.1101/2025.08.20.671303.
eQTL mapping and TWAS are widely used to contextualize GWAS, yet the impact of RNA-seq processing choices remains unexplored. We find that RNA-seq quantification method and transcriptomic reference substantially affect eQTL detection and gene expression prediction with significant downstream impact on colocalization and TWAS results. Our findings demonstrate that seemingly minor methodological decisions substantially affect these common analyses, highlighting the need for standardized practices to ensure reproducible genetic association studies.
表达数量性状基因座（eQTL）定位和全转录组关联研究（TWAS）被广泛用于阐释全基因组关联研究（GWAS），然而RNA测序（RNA-seq）处理选择的影响仍未得到探索。我们发现，RNA-seq定量方法和转录组参考对eQTL检测和基因表达预测有实质性影响，并对共定位和TWAS结果产生显著的下游影响。我们的研究结果表明，看似微小的方法学决策会对这些常见分析产生实质性影响，凸显了采用标准化方法以确保遗传关联研究可重复性的必要性。
