PINES

PINES prioritizes the functional impact of noncoding genetic variants by integrating phenotype-specific epigenetic annotations to refine functional characterization of the noncoding genome.


Key Features:

  • Phenotype-Informed Scoring: Leverages phenotype-dependent epigenetic and genomic information to score noncoding variants for functional relevance.
  • Epigenetic Annotation Integration: Incorporates epigenetic markers to contextualize variants within specific cellular environments.
  • Customizable Analysis: Enables analyses tailored to genomic annotations from cell types most relevant to the phenotype of interest to increase prediction specificity.

Scientific Applications:

  • Gene regulation analysis: Prioritizes noncoding variants that may affect regulatory elements and gene expression.
  • Disease mechanism investigation: Identifies phenotype-relevant noncoding variants implicated in disease mechanisms.
  • Genetic association studies: Refines interpretation of noncoding variants in GWAS and other genetic studies.
  • Precision medicine research: Supports phenotype-specific variant prioritization relevant to personalized medicine efforts.

Methodology:

Integrates epigenetic data in a phenotype-informed manner and prioritizes genomic annotations from cell types most relevant to the specified phenotype to improve precision of functional variant identification.

Topics

Collections

Details

Tool Type:
command-line tool, web application
Added:
1/20/2021
Last Updated:
5/18/2021

Operations

Publications

Bodea CA, Mitchell AA, Bloemendal A, Day-Williams AG, Runz H, Sunyaev SR. PINES: phenotype-informed tissue weighting improves prediction of pathogenic noncoding variants. Genome Biology. 2018;19(1). doi:10.1186/s13059-018-1546-6. PMID:30359302. PMCID:PMC6203199.