State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Biomedical Pioneering Innovative Center (BIOPIC) & Beijing Advanced Innovation Center for Genomics (ICG), Center for Bioinformatics (CBI), Peking University, Beijing 100871, China.
State Key Laboratory of Membrane Biology, Institute of Molecular Medicine, Peking University, Beijing 100871, China.
Genomics Proteomics Bioinformatics. 2023 Jun;21(3):662-673. doi: 10.1016/j.gpb.2021.10.003. Epub 2021 Dec 7.
Large-scale genome-wide association studies (GWAS) and expression quantitative trait locus (eQTL) studies have identified multiple non-coding variants associated with genetic diseases by affecting gene expression. However, pinpointing causal variants effectively and efficiently remains a serious challenge. Here, we developed CARMEN, a novel algorithm to identify functional non-coding expression-modulating variants. Multiple evaluations demonstrated CARMEN's superior performance over state-of-the-art tools. Applying CARMEN to GWAS and eQTL datasets further pinpointed several causal variants other than the reported lead single-nucleotide polymorphisms (SNPs). CARMEN scales well with the massive datasets, and is available online as a web server at http://carmen.gao-lab.org.
大规模全基因组关联研究（GWAS）和表达数量性状基因座（eQTL）研究已经确定了多种非编码变异，这些变异通过影响基因表达与遗传疾病相关。然而，有效地确定因果变异仍然是一个严峻的挑战。在这里，我们开发了一种新的算法 CARMEN，用于识别功能的非编码表达调节变异。多项评估表明，CARMEN 的性能优于最先进的工具。将 CARMEN 应用于 GWAS 和 eQTL 数据集，进一步确定了除报告的主要单核苷酸多态性（SNP）之外的几个因果变异。CARMEN 可以很好地扩展到大规模数据集，并且可以作为一个网络服务器在线使用，网址是 http://carmen.gao-lab.org。
