clin.iobio

clin.iobio facilitates collaborative interpretation and prioritization of genomic variants to support clinical diagnostics by integrating sequencing quality assessment, phenotype-driven gene prioritization, and variant annotation from knowledge bases.


Key Features:

  • Integration with iobio Suite: Integrates tools from the iobio genomic visualization suite for genomic visualization and data handling.
  • Genomic Data Quality Review: Performs quality assessment of sequencing data from targeted or whole-genome sequencing.
  • Dynamic Phenotype-Driven Gene Prioritization: Prioritizes genes dynamically using patient phenotype information.
  • Variant Prioritization with Comprehensive Knowledge Bases: Annotates and ranks variants using multiple knowledge bases, gene-phenotype associations, and computational evidence of pathogenicity.
  • Exportable Findings Summary: Generates exportable summaries of genomic findings for reporting and downstream review.

Scientific Applications:

  • Clinical variant identification: Streamlines identification of causative genetic variants in diagnostic settings.
  • Translation to patient care: Supports interpretation of genomic findings into actionable insights for precision medicine and clinical decision-making.

Methodology:

Integrates iobio suite tools with sequencing quality assessment, dynamic phenotype-driven gene prioritization, and variant annotation/prioritization using multiple knowledge bases and computational pathogenicity evidence.

Topics

Details

Cost:
Free of charge
Tool Type:
workflow
Operating Systems:
Mac, Linux, Windows
Added:
6/10/2022
Last Updated:
6/10/2022

Operations

Publications

Ward A, Velinder M, Di Sera T, Ekawade A, Malone Jenkins S, Moore B, Mao R, Bayrak-Toydemir P, Marth G. Clin.iobio: A Collaborative Diagnostic Workflow to Enable Team-Based Precision Genomics. Journal of Personalized Medicine. 2022;12(1):73. doi:10.3390/jpm12010073. PMID:35055388. PMCID:PMC8780189.

PMID: 35055388
PMCID: PMC8780189
Funding: - National Human Genome Research Institute: 5R01HG009712