Degree Adjusted Large-Scale Network Analysis Reveals Novel Putative Metabolic Disease Genes.

ABSTRACT: A large percentage of the global population is currently afflicted by metabolic diseases (MD), and the incidence is likely to double in the next decades. MD associated co-morbidities such as non-alcoholic fatty liver disease (NAFLD) and cardiomyopathy contribute significantly to impaired health. MD are complex, polygenic, with many genes involved in its aetiology. A popular approach to investigate genetic contributions to disease aetiology is biological network analysis. However, data dependence introduces a bias (noise, false positives, over-publication) in the outcome. While several approaches have been proposed to overcome these biases, many of them have constraints, including data integration issues, dependence on arbitrary parameters, database dependent outcomes, and computational com

SUBMITTER: Badkas A 

PROVIDER: S-EPMC7913176 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature