SysBiolPGWAS: simplifying post-GWAS analysis through the use of computational technologies and integration of diverse omics datasets

dc.contributor.authorAjayi, O
dc.date.accessioned2023-03-16T10:34:29Z
dc.date.available2023-03-16T10:34:29Z
dc.date.issued2022
dc.description.abstractMotivation: Post-genome-wide association studies (pGWAS) analysis is designed to decipher the functional consequences of significant single-nucleotide polymorphisms (SNPs) in the era of GWAS. This can be translated into research insights and clinical benefits such as the effectiveness of strategies for disease screening, treatment and prevention. However, the setup of pGWAS (pGWAS) tools can be quite complicated, and it mostly requires big data. The challenge however is, scientists are required to have sufficient experience with several of these technically complex and complicated tools in order to complete the pGWAS analysis. Results: We present SysBiolPGWAS, a pGWAS web application that provides a comprehensive functionality for biologists and non-bioinformaticians to conduct several pGWAS analyses to overcome the above challenges. It provides unique functionalities for analysis involving multi-omics datasets and visualization using various bioinformatics tools.en_US
dc.identifier.citationFalola, O., Adam, Y., Ajayi, O., Kumuthini, J., Adewale, S., Mosaku, A., Samtal, C., Adebayo, G., Emmanuel, J., Tchamga, M.S.S., Erondu, U., Nehemiah, A., Rasaq, S., Ajayi, M., Akanle, B., Oladipo, O., Isewon, I., Adebiyi, M., Oyelade, J., Adebiyi, E., 2023. SysBiolPGWAS: simplifying post-GWAS analysis through the use of computational technologies and integration of diverse omics datasets. Bioinformatics 39, btac791. https://doi.org/10.1093/bioinformatics/btac791en_US
dc.identifier.issn1367-4811
dc.identifier.urihttp://hdl.handle.net/10566/8611
dc.language.isoenen_US
dc.publisherBioinformaticsen_US
dc.subjectpost-gwas analysisen_US
dc.subjectcomputational technologiesen_US
dc.subjectsingle-nucleotide polymorphismsen_US
dc.subjectautosomal chromosomesen_US
dc.subjectomics datasetsen_US
dc.titleSysBiolPGWAS: simplifying post-GWAS analysis through the use of computational technologies and integration of diverse omics datasetsen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Ajayi_simplifying_post-gwas_analysis.pdf
Size:
514.69 KB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: