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NGSEA:基于网络的基因集富集分析,用于解释具有功能基因集的基因表达表型。

NGSEA: Network-Based Gene Set Enrichment Analysis for Interpreting Gene Expression Phenotypes with Functional Gene Sets.

机构信息

Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 03722, Korea.

Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul 03722, Korea.

出版信息

Mol Cells. 2019 Aug 31;42(8):579-588. doi: 10.14348/molcells.2019.0065.

Abstract

Gene set enrichment analysis (GSEA) is a popular tool to identify underlying biological processes in clinical samples using their gene expression phenotypes. GSEA measures the enrichment of annotated gene sets that represent biological processes for differentially expressed genes (DEGs) in clinical samples. GSEA may be suboptimal for functional gene sets; however, because DEGs from the expression dataset may not be functional genes but dysregulated genes perturbed by functional genes. To overcome this shortcoming, we developed network-based GSEA (NGSEA), which measures the enrichment score of functional gene sets using the expression difference of not only individual genes but also their neighbors in the functional network. We found that NGSEA outperformed GSEA in identifying pathway gene sets for matched gene expression phenotypes. We also observed that NGSEA substantially improved the ability to retrieve known anti-cancer drugs from patient-derived gene expression data using drug-target gene sets compared with another method, Connectivity Map. We also repurposed FDA-approved drugs using NGSEA and experimentally validated budesonide as a chemical with anti-cancer effects for colorectal cancer. We, therefore, expect that NGSEA will facilitate both pathway interpretation of gene expression phenotypes and anti-cancer drug repositioning. NGSEA is freely available at www.inetbio.org/ngsea.

摘要

基因集富集分析(GSEA)是一种使用基因表达表型来识别临床样本中潜在生物学过程的流行工具。GSEA 测量注释基因集的富集程度,这些基因集代表临床样本中差异表达基因(DEGs)的生物学过程。GSEA 可能不适合功能基因集;然而,由于表达数据集的 DEGs 可能不是功能基因,而是受功能基因扰动的失调基因。为了克服这一缺点,我们开发了基于网络的 GSEA(NGSEA),它使用功能网络中不仅单个基因而且其邻居的表达差异来测量功能基因集的富集分数。我们发现,与另一种方法 Connectivity Map 相比,NGSEA 在识别匹配基因表达表型的途径基因集方面表现优于 GSEA。我们还观察到,与另一种方法 Connectivity Map 相比,使用药物-靶基因集,NGSEA 大大提高了从患者衍生的基因表达数据中检索已知抗癌药物的能力。我们还使用 NGSEA 重新利用了 FDA 批准的药物,并通过实验验证了布地奈德作为一种对结直肠癌有抗癌作用的化学物质。因此,我们预计 NGSEA 将有助于基因表达表型的途径解释和抗癌药物的重新定位。NGSEA 可在 www.inetbio.org/ngsea 上免费获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c1f/6715341/d9dac88e5889/molce-42-579f1.jpg

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