{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["de Maturana EL"],"funding":["NCI NIH HHS"],"pagination":["e83745"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC3877090"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["8(12)"],"pubmed_abstract":["The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988 controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration with the widely used univariate logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold LASSO (BTL), a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs "],"journal":["PloS one"],"pubmed_title":["Application of multi-SNP approaches Bayesian LASSO and AUC-RF to detect main effects of inflammatory-gene variants associated with bladder cancer risk."],"pmcid":["PMC3877090"],"funding_grant_id":["R01 CA 131335","P50 CA091846","R01 CA089715","U01 CA 127615","U01 CA127615","R01 CA131335","R01 CA 74880","R01 CA034627","P50 CA 91846","R01- CA089715","R01 CA074880","CA34627"],"pubmed_authors":["Chanock SJ","Gonzalez-Neira A","Garcia-Closas M","Tardon A","Petrus S","Kogevinas M","de Maturana EL","Urrea V","Carrato A","Ye Y","Calle ML","Silverman DT","Rothman N","Lorente-Galdos B","Real FX","Vellalta G","Malats N","Navarro A","Wu X"],"additional_accession":[]},"is_claimable":false,"name":"Application of multi-SNP approaches Bayesian LASSO and AUC-RF to detect main effects of inflammatory-gene variants associated with bladder cancer risk.","description":"The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988 controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration with the widely used univariate logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold LASSO (BTL), a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs ","dates":{"release":"2013-01-01T00:00:00Z","publication":"2013","modification":"2026-05-02T09:28:21.155Z","creation":"2019-03-26T23:25:30Z"},"accession":"S-EPMC3877090","cross_references":{"pubmed":["24391818"],"doi":["10.1371/journal.pone.0083745"]}}