{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Cheng S"],"funding":["NIEHS NIH HHS","NLM NIH HHS","NCI NIH HHS","National Institutes of Health"],"pagination":["40"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC5154053"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["9"],"pubmed_abstract":["<h4>Background</h4>Bladder cancer is common disease with a complex etiology that is likely due to many different genetic and environmental factors. The goal of this study was to embrace this complexity using a bioinformatics analysis pipeline designed to use machine learning to measure synergistic interactions between single nucleotide polymorphisms (SNPs) in two genome-wide association studies (GWAS) and then to assess their enrichment within functional groups defined by Gene Ontology. The significance of the results was evaluated using permutation testing and those results that replicated between the two GWAS data sets were reported.<h4>Results</h4>In the first step of our bioinformatics pipeline, we estimated the pairwise synergistic effects of SNPs on bladder cancer risk in both GWAS d"],"journal":["BioData mining"],"pubmed_title":["Complex systems analysis of bladder cancer susceptibility reveals a role for decarboxylase activity in two genome-wide association studies."],"pmcid":["PMC5154053"],"funding_grant_id":["R21 CA182659","R01 LM010098","R01 LM009012","P30 ES013508"],"pubmed_authors":["Cheng S","Moore JH","Andrews PC","Andrew AS"],"additional_accession":[]},"is_claimable":false,"name":"Complex systems analysis of bladder cancer susceptibility reveals a role for decarboxylase activity in two genome-wide association studies.","description":"<h4>Background</h4>Bladder cancer is common disease with a complex etiology that is likely due to many different genetic and environmental factors. The goal of this study was to embrace this complexity using a bioinformatics analysis pipeline designed to use machine learning to measure synergistic interactions between single nucleotide polymorphisms (SNPs) in two genome-wide association studies (GWAS) and then to assess their enrichment within functional groups defined by Gene Ontology. The significance of the results was evaluated using permutation testing and those results that replicated between the two GWAS data sets were reported.<h4>Results</h4>In the first step of our bioinformatics pipeline, we estimated the pairwise synergistic effects of SNPs on bladder cancer risk in both GWAS d","dates":{"release":"2016-01-01T00:00:00Z","publication":"2016","modification":"2025-04-27T00:40:55.362Z","creation":"2019-03-27T02:31:22Z"},"accession":"S-EPMC5154053","cross_references":{"pubmed":["27999618"],"doi":["10.1186/s13040-016-0119-z"]}}