摘要
Objective: The objective of this work is to search for a novel method to explore the disrupted pathways associated with periodontitis(PD) based on the network level.Methods: Firstly, the differential expression genes(DEGs) between PD patients and cognitively normal subjects were inferred based on LIMMA package. Then, the proteinprotein interactions(PPI) in each pathway were explored by Empirical Bayesian(EB) coexpression program. Specifically, we determined the 100 th weight value as the threshold value of the disrupted pathways of PPI by constructing the randomly model and confirmed the weight value of each pathway. Meanwhile, we dissected the disrupted pathways under the weight value > the threshold value. Pathways enrichment analyses of DEGs were carried out based on Expression Analysis Systematic Explored(EASE) test. Finally, the better method was selected based on the more rich and significant obtained pathways by comparing the two methods. Results: After the calculation of LIMMA package, we estimated 524 DEGs in all. Then we determined 0.115222 as the threshold value of the disrupted pathways of PPI. When the weight value>0.115222, there were 258 disrupted pathways of PPI enriched in. Additionally, we observed those 524 DEGs that were enriched in 4 pathways under EASE=0.1.Conclusion: We proposed a novel network method inferring the disrupted pathway for PD. The disrupted pathways might be underlying biomarkers for treatment associated with PD.
Objective： The objective of this work is to search for a novel method to explore the disrupted pathways associated with periodontitis （PD） based on the network level.Methods： Firstly, the differential expression genes （DEGs） between PD patients and cognitively normal subjects were inferred based on LIMMA package. Then, the protein-protein interactions （PPI） in each pathway were explored by Empirical Bayesian （EB） co-expression program. Specifcally, we determined the 100th weight value as the threshold value of the disrupted pathways of PPI by constructing the randomly model and confrmed the weight value of each pathway. Meanwhile, we dissected the disrupted pathways under the weight value 〉 the threshold value. Pathways enrichment analyses of DEGs were carried out based on Expression Analysis Systematic Explored （EASE） test. Finally, the beter method was selected based on the more rich and signifcant obtained pathways by comparing the two methods. Results： After the calculation of LIMMA package, we estimated 524 DEGs in all. Then we determined 0.115222 as the threshold value of the disrupted pathways of PPI. When the weight value〉0.115222, there were 258 disrupted pathways of PPI enriched in. Additionally, we observed those 524 DEGs that were enriched in 4 pathways underEASE=0.1.Conclusion： We proposed a novel network method inferring the disrupted pathway for PD. Te disrupted pathways might be underlying biomarkers for treatment associated with PD.
出处
《国际感染病学（电子版）》
CAS
2016年第4期93-98,共6页
Infection International(Electronic Edition)
