| Autor: |
Jing Tang, Yongheng Wang, Jianbo Fu, Xianglu Wu, Zhijie Han, Chuan Wang, Maiyuan Guo, Yingxiong Wang, Yubin Ding, Bo Yang, Feng Zhu |
| Předmět: |
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| Zdroj: |
Quantitative Biology; Dec2021, Vol. 9 Issue 4, p411-425, 15p |
| Abstrakt: |
Background: Functional characterization of the long noncoding RNAs (lncRNAs) in disease attracts great attention, which results in a limited number of experimentally characterized lncRNAs. 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 lncRNA 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 lncRNAs, (3) weighted correlation network of lncRNAs and protein-coding neighboring genes. Results: FCCLnc can characterize lncRNA 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 lncRNA-centered co-expression network. Conclusion: In summary, FCCLnc is unique in characterizing lncRNA function in diverse diseases and comorbidities and is highly expected to emerge to be an indispensable complement to other available tools. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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