Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
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DOI：
10.1073/pnas.0506580102
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发表时间：
2005-10-25
影响因子：
11.1
通讯作者：
Mesirov, JP
中科院分区：
文献类型：
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作者：
Subramanian, A;Tamayo, P;Mesirov, JP
尽管全基因组 RNA 表达分析已成为生物医学研究的常规工具，但从此类信息中提取生物学见解仍然是一项重大挑战。在这里，我们描述了一种强大的分析方法，称为基因集富集分析（GSEA），用于解释基因表达数据。该方法通过关注基因集（即具有共同生物功能、染色体位置或调控的基因组）来发挥其作用。我们展示了 GSEA 如何深入了解多种癌症相关数据集，包括白血病和肺癌。值得注意的是，单基因分析发现两项关于肺癌患者生存的独立研究之间几乎没有相似之处，而 GSEA 揭示了许多共同的生物学途径。 GSEA 方法包含在一个免费提供的软件包中，以及包含 1,325 个生物学定义的基因集的初始数据库。
Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.