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Functional characterization of disease/comorbidity-associated IncRNA
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作者 Jing Tang Yongheng Wang +8 位作者 Jianbo Fu xianglu wu Zhijie Han Chuan Wang Maiyuan Guo Yingxiong Wang Yubin Ding Bo Yang Feng Zhu 《Quantitative Biology》 CSCD 2021年第4期411-425,共15页
Background:Functional characterization of the long noncoding RNAs(IncRNAs)in disease attracts great attention,which results in a limited number of experimentally characterized IncRNAs.The major problems underlying the... Background:Functional characterization of the long noncoding RNAs(IncRNAs)in disease attracts great attention,which results in a limited number of experimentally characterized IncRNAs.The major problems underlying the lack of experimental verifications are considered to come from the significant false-positive assignments and extensive genetic-heterogeneity of disease.These problems are even worse when it comes to the functional characterization in comorbidity(simultaneous/sequential presence of multiple diseases in a patient,and showing much wider prevalence,poorer treatment-response and longer illness-course than a single disease).Methods:Herein,FCCLnc was developed to characterize IncRNA function by(1)integrating diverse SNPs that were associated with 193 diseases standardized by International Classification of Diseases(ICD-11),(2)condition-specific expression of IncRNAs,(3)weighted correlation network of IncRNAs and protein-coding neighboring genes.Results:FCCLnc can characterize IncRNA function in both disease and comorbidity by not only controlling false discovery but also tolerating their disease heterogeneity.Moreover,FCCLnc can provide interactive visualization and full download of IncRNA-centered co-expression network.Conclusion:In summary,FCCLnc is unique in characterizing IncRNA function in diverse diseases and comorbidities and is highly expected to emerge to be an indispensable complement to other available tools.FCCLnc is accessible at https://idrblab.org/fcclnc/. 展开更多
关键词 COMORBIDITY long noncoding RNA functional characterization disease-associated SNPs guilt-by-association
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