Data-Driven-Based Approach to Identifying Differentially Methylated Regions Using Modified 1D Ising Model
المؤلفون المشاركون
Wang, Shudong
Zhang, Yuanyuan
Wang, Xinzeng
المصدر
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-11-18
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
Background.
DNA methylation is essential for regulating gene expression, and the changes of DNA methylation status are commonly discovered in disease.
Therefore, identification of differentially methylation patterns, especially differentially methylated regions (DMRs), in two different groups is important for understanding the mechanism of complex diseases.
Few tools exist for DMR identification through considering features of methylation data, but there is no comprehensive integration of the characteristics of DNA methylation data in current methods.
Results.
Accounting for the characteristics of methylation data, such as the correlation characteristics of neighboring CpG sites and the high heterogeneity of DNA methylation data, we propose a data-driven approach for DMR identification through evaluating the energy of single site using modified 1D Ising model.
Applied to both simulated and publicly available datasets, our approach is compared with other popular methods in terms of performance.
Simulated results show that our method is more sensitive than competing methods.
Applied to the real data, our method can identify more common DMRs than DMRcate, ProbeLasso, and Wang’s methods with a high overlapping ratio.
Also, the necessity of integrating the heterogeneity and correlation characteristics in identifying DMR is shown through comparing results with only considering mean or variance signals and without considering relationship of neighboring CpG sites, respectively.
Through analyzing the number of DMRs identified in real data located in different genomic regions, we find that about 90% DMRs are located in CGI which always regulates the expression of genes.
It may help us understand the functional effect of DNA methylation on disease.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhang, Yuanyuan& Wang, Shudong& Wang, Xinzeng. 2018. Data-Driven-Based Approach to Identifying Differentially Methylated Regions Using Modified 1D Ising Model. BioMed Research International،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1124140
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhang, Yuanyuan…[et al.]. Data-Driven-Based Approach to Identifying Differentially Methylated Regions Using Modified 1D Ising Model. BioMed Research International No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1124140
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhang, Yuanyuan& Wang, Shudong& Wang, Xinzeng. Data-Driven-Based Approach to Identifying Differentially Methylated Regions Using Modified 1D Ising Model. BioMed Research International. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1124140
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1124140
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر