A compendium of uniformly processed human gene expression and splicing quantitative trait loci.
A compendium of uniformly processed human gene expression and splicing quantitative trait loci.
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DOI：
10.1038/s41588-021-00924-w
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发表时间：
2021-09
期刊：
影响因子：
30.8
通讯作者：
Alasoo K
中科院分区：
文献类型：
--
作者：
Kerimov N;Hayhurst JD;Peikova K;Manning JR;Walter P;Kolberg L;Samoviča M;Sakthivel MP;Kuzmin I;Trevanion SJ;Burdett T;Jupp S;Parkinson H;Papatheodorou I;Yates AD;Zerbino DR;Alasoo K
许多基因表达数量性状基因座（eQTL）研究已经发表了其汇总统计量，这些汇总统计量可以通过精细定位和共定位等下游分析来深入了解复杂的人类性状。然而，这些数据集之间的技术差异是其广泛使用的障碍。因此，大多数全基因组关联研究（GWAS）信号的靶基因仍未确定。在本研究中，我们提出了eQTL目录（https：//www.ebi.ac.uk/eqtl），这是一个来自21项研究的质量控制、统一重新计算的基因表达和剪接QTL的资源。我们发现，对于匹配的细胞类型和组织，eQTL效应大小在研究之间是高度可重复的。虽然大多数QTL之间共享的大多数散装组织，我们确定了一个更大的细胞类型特异性QTL的多样性从纯化的细胞类型，其中一个子集也表现为新的疾病共定位。我们的汇总统计数据可免费获得，以系统地解释人类GWAS在许多细胞类型和组织中的关联。eQTL目录提供了21个eQTL研究的统一处理，允许鉴定影响全基因和转录本表达水平的高度可重复的eQTL。
Many gene expression quantitative trait locus (eQTL) studies have published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization. However, technical differences between these datasets are a barrier to their widespread use. Consequently, target genes for most genome-wide association study (GWAS) signals have still not been identified. In the present study, we present the eQTL Catalogue (https://www.ebi.ac.uk/eqtl), a resource of quality-controlled, uniformly re-computed gene expression and splicing QTLs from 21 studies. We find that, for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies. Although most QTLs were shared between most bulk tissues, we identified a greater diversity of cell-type-specific QTLs from purified cell types, a subset of which also manifested as new disease co-localizations. Our summary statistics are freely available to enable the systematic interpretation of human GWAS associations across many cell types and tissues. The eQTL Catalogue provides uniform processing of 21 eQTL studies, allowing the identification of highly reproducible eQTLs affecting whole gene and transcript expression levels.
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影响因子：
30.8
作者：
Das, Sayantan;Forer, Lukas;Schoenherr, Sebastian;Sidore, Carlo;Locke, Adam E.;Kwong, Alan;Vrieze, Scott I.;Chew, Emily Y.;Levy, Shawn;McGue, Matt;Schlessinger, David;Stambolian, Dwight;Loh, Po-Ru;Iacono, William G.;Swaroop, Anand;Scott, Laura J.;Cucca, Francesco;Kronenberg, Florian;Boehnke, Michael;Abecasis, Goncalo R.;Fuchsberger, Christian
通讯作者：
Fuchsberger, Christian
影响因子：
30.8
作者：
Fairfax, Benjamin P.;Makino, Seiko;Radhakrishnan, Jayachandran;Plant, Katharine;Leslie, Stephen;Dilthey, Alexander;Ellis, Peter;Langford, Cordelia;Vannberg, Fredrik O.;Knight, Julian C.
通讯作者：
Knight, Julian C.
影响因子：
9.2
作者：
Chang CC;Chow CC;Tellier LC;Vattikuti S;Purcell SM;Lee JJ
通讯作者：
Lee JJ
影响因子：
64.5
作者：
Astle, William J.;Elding, Heather;Soranzo, Nicole
通讯作者：
Soranzo, Nicole
影响因子：
30.8
作者：
Bentham J;Morris DL;Graham DSC;Pinder CL;Tombleson P;Behrens TW;Martín J;Fairfax BP;Knight JC;Chen L;Replogle J;Syvänen AC;Rönnblom L;Graham RR;Wither JE;Rioux JD;Alarcón-Riquelme ME;Vyse TJ
通讯作者：
Vyse TJ