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e-GRASP: an integrated evolutionary and GRASP resource for exploring disease associations.

Sajjad Karim1, Hend Fakhri NourEldin1, Heba Abusamra1

  • 1Center for Excellence in Genome Medicine and Research, King Abdulaziz University, Jeddah, Saudi Arabia.

BMC Genomics
|October 22, 2016
PubMed
Summary

This study introduces e-GRASP, a new resource that combines genome-wide association study (GWAS) data with evolutionary information. It helps researchers identify reliable genetic associations for complex diseases by considering evolutionary conservation.

Keywords:
ConservationDiseaseGRASPGWASPhenotypePolymorphismSNP

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Area of Science:

  • Genomics
  • Evolutionary Biology
  • Bioinformatics

Background:

  • Genome-wide association studies (GWAS) identify genetic variations linked to traits and diseases.
  • Prioritizing reproducible genetic associations from GWAS remains a challenge.
  • Evolutionary-aware meta-analysis can help advance from association to causation.

Purpose of the Study:

  • To create an evolutionary GWAS resource (e-GRASP) for exploring published GWAS results.
  • To integrate evolutionary information with existing GWAS data.
  • To enhance the discovery of biologically meaningful genotype-phenotype relationships.

Main Methods:

  • Utilized the GRASP2 database containing 2082 studies and ~8.87 million SNP-phenotype associations.
  • Annotated SNPs with evolutionary information, including conservation rates and timespans.
  • Developed an evolutionary-adjusted SNP association ranking (E-rank) using conservation scores and allele frequencies.

Main Results:

  • The e-GRASP resource provides integrated GWAS and evolutionary data for millions of SNP-phenotype associations.
  • Users can identify SNPs based on statistical significance, replication, and evolutionary conservation.
  • The E-rank metric aims to improve the discovery of functionally important SNPs.

Conclusions:

  • e-GRASP enhances the exploration of GWAS results by incorporating evolutionary context.
  • The resource aids researchers in identifying bona fide and reproducible genetic associations.
  • e-GRASP is freely available at http://www.mypeg.info/egrasp for broader scientific use.