A clinical knowledge graph-based framework to prioritize candidate genes for facilitating diagnosis of Mendelian diseases and rare genetic conditions.

ABSTRACT:

Background

Diagnosing Mendelian and rare genetic conditions requires identifying phenotype-associated genetic findings and prioritizing likely disease-causing genes. This task is labor-intensive for molecular and clinical geneticists, who must review extensive literature and databases to link patient phenotypes with causal genotypes. The challenge is further complicated by the large number of genetic variants detected through next-generation sequencing, which impacts both diagnosis timelines and patient care strategies. To address this, in silico methods that prioritize causal genes based on patient-derived phenotypes offer an effective solution, reducing the time involved in diagnostic case reviews and enhancing the efficiency of clinical diagnosis.

Results

We developed the

SUBMITTER: Gnanaolivu R 

PROVIDER: S-EPMC11908102 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature