Factors affecting interactome-based prediction of human genes associated with clinical signs.

ABSTRACT:

Background

Clinical signs are a fundamental aspect of human pathologies. While disease diagnosis is problematic or impossible in many cases, signs are easier to perceive and categorize. Clinical signs are increasingly used, together with molecular networks, to prioritize detected variants in clinical genomics pipelines, even if the patient is still undiagnosed. Here we analyze the ability of these network-based methods to predict genes that underlie clinical signs from the human interactome.

Results

Our analysis reveals that these approaches can locate genes associated with clinical signs with variable performance that depends on the sign and associated disease. We analyzed several clinical and biological factors that explain these variable results, including number of genes

SUBMITTER: Gonzalez-Perez S 

PROVIDER: S-EPMC5514523 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature