miR2Trait: an integrated resource for investigating miRNA-disease associations

PeerJ

article

Poornima Babu¹  Ashok Palaniappan¹ 

[1] Department of Bioinformatics, School of Chemical and Biotechnology, SASTRA University

关键词: miRNA;    Enrichment analysis;    Network analysis;    Diseasome;    Webserver;    Gene regulation;    Disease genes;    miRNA-disease associations;    Knowledge base;   

DOI  :  10.7717/peerj.14146

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

MicroRNAs are key components of cellular regulatory networks, and breakdown in miRNA function causes cascading effects leading to pathophenotypes. A better understanding of the role of miRNAs in diseases is essential for human health. Here, we have devised a method for comprehensively mapping the associations between miRNAs and diseases by merging on a common key between two curated omics databases. The resulting bidirectional resource, miR2Trait, is more detailed than earlier catalogs, uncovers new relationships, and includes analytical utilities to interrogate and extract knowledge from these datasets. miR2Trait provides resources to compute the disease enrichment of a user-given set of miRNAs and analyze the miRNA profile of a specified diseasome. Reproducible examples demonstrating use-cases for each of these resource components are illustrated. Furthermore we used these tools to construct pairwise miRNA-miRNA and disease-disease enrichment networks, and identified 23 central miRNAs that could underlie major regulatory functions in the human genome. miR2Trait is available as an open-source command-line interface in Python3 (URL: https://github.com/miR2Trait) with a companion wiki documenting the scripts and data resources developed, under MIT license for commercial and non-commercial use. A minimal web-based implementation has been made available at https://sas.sastra.edu/pymir18. Supplementary information is available at: https://doi.org/10.6084/m9.figshare.8288825.v3.

【 授权许可】

CC BY