Variable Selection and Joint Estimation of Mean and Covariance Models with an Application to eQTL Data
المؤلفون المشاركون
Kim, SungHwan
Lee, JungJun
Jhong, Jae-Hwan
Koo, Ja-Yong
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-06-25
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
In genomic data analysis, it is commonplace that underlying regulatory relationship over multiple genes is hardly ascertained due to unknown genetic complexity and epigenetic regulations.
In this paper, we consider a joint mean and constant covariance model (JMCCM) that elucidates conditional dependent structures of genes with controlling for potential genotype perturbations.
To this end, the modified Cholesky decomposition is utilized to parametrize entries of a precision matrix.
The JMCCM maximizes the likelihood function to estimate parameters involved in the model.
We also develop a variable selection algorithm that selects explanatory variables and Cholesky factors by exploiting the combination of the GCV and BIC as benchmarks, together with Rao and Wald statistics.
Importantly, we notice that sparse estimation of a precision matrix (or equivalently gene network) is effectively achieved via the proposed variable selection scheme and contributes to exploring significant hub genes shown to be concordant to a priori biological evidence.
In simulation studies, we confirm that our model selection efficiently identifies the true underlying networks.
With an application to miRNA and SNPs data from yeast (a.k.a.
eQTL data), we demonstrate that constructed gene networks reproduce validated biological and clinical knowledge with regard to various pathways including the cell cycle pathway.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Lee, JungJun& Kim, SungHwan& Jhong, Jae-Hwan& Koo, Ja-Yong. 2018. Variable Selection and Joint Estimation of Mean and Covariance Models with an Application to eQTL Data. Computational and Mathematical Methods in Medicine،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1132029
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Lee, JungJun…[et al.]. Variable Selection and Joint Estimation of Mean and Covariance Models with an Application to eQTL Data. Computational and Mathematical Methods in Medicine No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1132029
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Lee, JungJun& Kim, SungHwan& Jhong, Jae-Hwan& Koo, Ja-Yong. Variable Selection and Joint Estimation of Mean and Covariance Models with an Application to eQTL Data. Computational and Mathematical Methods in Medicine. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1132029
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1132029
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