SysBiolPGWAS

SysBiolPGWAS performs post-genome-wide association study (pGWAS) analyses to interpret functional implications of significant single-nucleotide polymorphisms (SNPs) and to integrate multi-omics datasets for downstream biological interpretation.


Key Features:

  • Comprehensive pGWAS functionality: Suite of analyses for post-GWAS interpretation of significant single-nucleotide polymorphisms (SNPs).
  • Integration of multi-omics datasets: Supports integration and analysis of diverse omics datasets to link genetic associations with additional molecular layers.
  • Custom pGWAS pipeline: Implements a custom pipeline that integrates multiple individual pGWAS tools and datasets.
  • Visualization tools: Provides visualization capabilities using bioinformatics tools to facilitate interpretation of complex data outputs.

Scientific Applications:

  • Human autosomal variant interpretation: Interprets genetic associations on autosomal chromosomes to investigate functional consequences of SNPs.
  • High-throughput genomic studies: Handles large-scale datasets for high-throughput post-GWAS analyses.
  • Translational genomics and personalized medicine: Supports translation of genetic findings toward disease screening, treatment, and prevention strategies and personalized medicine applications.

Methodology:

Integration of multiple individual pGWAS tools and external datasets into a custom pipeline forming a cohesive platform for post-GWAS analyses.

Topics

Details

License:
Not licensed
Cost:
Free of charge
Tool Type:
web application
Operating Systems:
Mac, Linux, Windows
Programming Languages:
Fortran, Assembly language, C
Added:
2/10/2023
Last Updated:
11/24/2024

Operations

Data Inputs & Outputs

Publications

Falola O, Adam Y, Ajayi O, Kumuthini J, Adewale S, Mosaku A, Samtal C, Adebayo G, Emmanuel J, Tchamga MSS, Erondu U, Nehemiah A, Rasaq S, Ajayi M, Akanle B, Oladipo O, Isewon I, Adebiyi M, Oyelade J, Adebiyi E. SysBiolPGWAS: simplifying post-GWAS analysis through the use of computational technologies and integration of diverse omics datasets. Bioinformatics. 2022;39(1). doi:10.1093/bioinformatics/btac791. PMID:36477976. PMCID:PMC9825739.

PMID: 36477976
PMCID: PMC9825739
Funding: - National Human Genome Research Institute: U24HG006941, U2RTW010679

Links