EvORanker

EvORanker prioritizes candidate genes implicated in undiagnosed genetic disorders from next-generation sequencing by integrating multi-scale phylogenetic profiling across 1,028 eukaryotic genomes with clinical and other omics data.

Key Features:

• Integration of Unbiased Genomic Data: Integrates unbiased genomic data across 1,028 eukaryotic genomes to detect conserved signals relevant to human disease.
• Multi-Scale Phylogenetic Profiling: Employs multi-scale phylogenetic profiling, including clade-based approaches, to prioritize genes based on evolutionary conservation patterns.
• Utilization of Clinical and Omics Data: Combines clinical phenotype data with other omics datasets to inform and refine gene prioritization.
• Performance Evaluation: Validated on solved exomes and simulated genomes, identifying the true disease gene as the top candidate in 69% of cases and within the top five in 95%.
• Application to Knockout Genes: Applied to a dataset of 6,260 knockout genes with mouse phenotypes lacking human associations and linked 41% to observed human disease phenotypes.
• Case Studies: Recovered DLGAP2 and LPCAT3 as candidate genes in two previously unsolved genetic cases.

Scientific Applications:

• Gene prioritization from NGS/exome/genome data: Narrowing candidate disease-causing genes identified by next-generation sequencing and exome analysis.
• Annotation of poorly characterized genes: Linking poorly annotated or uncharacterized genes to human phenotypes via comparative genomics.
• Translation of model organism phenotypes: Interpreting mouse knockout phenotypes to propose human gene-disease associations.
• Discovery of novel gene-disease relationships: Supporting research and variant interpretation in clinical genomics and personalized medicine.

Methodology:

Performs multi-scale (including clade-based) phylogenetic profiling across 1,028 eukaryotic genomes and integrates those profiles with clinical phenotype and other omics data; evaluated on solved exomes and simulated genomes.