基于改进TF-IDF算法的基因通路富集方法-《中国医学物理学杂志》

文章信息/Info

作者:: 徐淑坦1; 2; 冷银辉1; 2; 陈明1; 2; 1.上海海洋大学信息学院，上海 201306； 2.农业农村部渔业信息重点实验室，上海 201306

Author(s):: XU Shutan1; 2; LENG Yinhui1; 2; CHEN Ming1; 2; 1. College of Information Technology, Shanghai Ocean University, Shanghai 201306, China 2.Key Laboratory of Fisheries Information, Ministry of Agriculture and Rural Affairs of the Peoples Republic of China, Shanghai 201306, China

摘要:: 提出一种综合考虑通路局部和全局信息的基因通路富集分析（GIGSEA）方法。首先利用基因相互作用数据，通过基因在通路的局部重要性和在通路数据库的全局特异性计算基因的影响力；然后将基因影响力和表型相关性值融合在一起，计算通路的富集分数；最后通过置换基因富集出统计学显著的通路。将GIGSEA方法运用于肝细胞癌和结肠直肠癌数据集进行风险通路富集，与基因集富集分析方法相比，GIGSEA方法能富集出一些新的相关通路，并排除无关的通路，提高疾病相关通路的富集效果。

Abstract:: A gene pathway enrichment method (GIGSEA method) that comprehensively considers the local and global information of the pathways is proposed. The gene interaction data are used to calculate the gene impact based on the local importance of the gene in the pathway and its global specificity in the pathway database. Then the obtained gene impact is fused with the phenotypic correlation value to calculate enrichment score, and statistically significant pathways are identified by permutating gene. GIGSEA is applied to the data sets of hepatocellular carcinoma and colorectal cancer for the enrichment of risk pathways. Compared with the gene set enrichment analysis method, GIGSEA method can enrich some new related pathways and exclude irrelevant pathways, which improves the enrichment effect of disease-associated pathways.