基于数据融合算法的精神分裂症易感基因排序及其信号通路研究

Gene ranking and signaling pathway of schizophrenia susceptible genes based on data fusion arithmetic

目的利用已有的研究结果,采用数据融合分析方法,对与已知的精神分裂症易感基因有密切关系的候选基因进行统计分析,得出基因排序及其信号通路的结果,以此证明数据融合算法能够有效筛选精神分裂症易感基因。方法根据已知的与精神分裂症相关的基因,利用Endeavour工具,通过数据融合算法将候选基因排序,并用DAVID数据库对基因排序结果进行功能注释和富集分析。结果利用数据融合算法获得的排序较高的基因与已有研究进行比较,证实排名第二的NRG3和排名第三的AKT1与精神分裂症有密切联系。其他排名较高的基因可以作为潜在的疾病易感基因,为精神分裂症的研究提供参考。结论数据融合算法能够准确评价候选基因与精神分裂症的联系,使用该方法能有效地对精神分裂症易感基因进行筛选和判定。

Objective Based on previous studies,this paper applies data fusion arithmetic to extract the potential susceptible genes and signaling pathway related to schizophrenia, which proves that data fusion algorithm is an effective method to filter schizophrenia susceptible genes. Methods By making use of Endeavour tool which is based on data fusion method,the candidate genes were ranked according to their similarity with the tralning genes. Then DAVID database was used to implement the functional annotation and enrichment analysis for the extracted genes. Results Compared with previous studies,the second NRG3 and third AKT1 which are obtalned from higher ranking candidate genes,are closely related to schizophrenia. Other higher ranking genes could be used as potential disease-susceptibility genes to provide reference for the research of schizophrenia. Conclusions Data fusion arithmetic can help to detect the potential schizophrenia candidate genes objectively and correctly,and this method is a powerful tool for identifying schizophrenia susceptible genes.