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Genome-wide functional association networks: background, data & state-of-the-art resources.

ABSTRACT: The vast amount of experimental data from recent advances in the field of high-throughput biology begs for integration into more complex data structures such as genome-wide functional association networks. Such networks have been used for elucidation of the interplay of intra-cellular molecules to make advances ranging from the basic science understanding of evolutionary processes to the more translational field of precision medicine. The allure of the field has resulted in rapid growth of the number of available network resources, each with unique attributes exploitable to answer different biological questions. Unfortunately, the high volume of network resources makes it impossible for the intended user to select an appropriate tool for their particular research question. The aim of this paper is to provide an overview of the underlying data and representative network resources as well as to mention methods of integration, allowing a customized approach to resource selection. Additionally, this report will provide a primer for researchers venturing into the field of network integration.

SUBMITTER: Guala D

PROVIDER: S-EPMC7373183 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Genome-wide functional association networks: background, data & state-of-the-art resources.

Guala Dimitri D Ogris Christoph C Müller Nikola N Sonnhammer Erik L L ELL

Briefings in bioinformatics 20200701 4

The vast amount of experimental data from recent advances in the field of high-throughput biology begs for integration into more complex data structures such as genome-wide functional association networks. Such networks have been used for elucidation of the interplay of intra-cellular molecules to make advances ranging from the basic science understanding of evolutionary processes to the more translational field of precision medicine. The allure of the field has resulted in rapid growth of the n ...[more]

PMID: 31281921

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Project description:Pathway analysis of genome-wide association studies (GWAS) offer a unique opportunity to collectively evaluate genetic variants with effects that are too small to be detected individually. We applied a pathway analysis to a bladder cancer GWAS containing data from 3,532 cases and 5,120 controls of European background (n?=?5 studies). Thirteen hundred and ninety-nine pathways were drawn from five publicly available resources (Biocarta, Kegg, NCI-PID, HumanCyc, and Reactome), and we constructed 22 additional candidate pathways previously hypothesized to be related to bladder cancer. In total, 1421 pathways, 5647 genes and ?90,000 SNPs were included in our study. Logistic regression model adjusting for age, sex, study, DNA source, and smoking status was used to assess the marginal trend effect of SNPs on bladder cancer risk. Two complementary pathway-based methods (gene-set enrichment analysis [GSEA], and adapted rank-truncated product [ARTP]) were used to assess the enrichment of association signals within each pathway. Eighteen pathways were detected by either GSEA or ARTP at P?0.01. To minimize false positives, we used the I(2) statistic to identify SNPs displaying heterogeneous effects across the five studies. After removing these SNPs, seven pathways ('Aromatic amine metabolism' [P(GSEA)?=?0.0100, P(ARTP)?=?0.0020], 'NAD biosynthesis' [P(GSEA)?=?0.0018, P(ARTP)?=?0.0086], 'NAD salvage' [P(ARTP)?=?0.0068], 'Clathrin derived vesicle budding' [P(ARTP)?=?0.0018], 'Lysosome vesicle biogenesis' [P(GSEA)?=?0.0023, P(ARTP)<0.00012], 'Retrograde neurotrophin signaling' [P(GSEA)?=?0.00840], and 'Mitotic metaphase/anaphase transition' [P(GSEA)?=?0.0040]) remained. These pathways seem to belong to three fundamental cellular processes (metabolic detoxification, mitosis, and clathrin-mediated vesicles). Identification of the aromatic amine metabolism pathway provides support for the ability of this approach to identify pathways with established relevance to bladder carcinogenesis.

Dataset Information

Genome-wide functional association networks: background, data & state-of-the-art resources.

Publications

Genome-wide functional association networks: background, data & state-of-the-art resources.

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