Detecting significant single-nucleotide polymorphisms in a rheumatoid arthritis study using random forests
Wang M, Chen X, Zhang M, Zhu W, Cho K, Zhang H. Detecting significant single-nucleotide polymorphisms in a rheumatoid arthritis study using random forests. BMC Proceedings 2009, 3: s69. PMID: 20018063, PMCID: PMC2795970, DOI: 10.1186/1753-6561-3-s7-s69.Peer-Reviewed Original ResearchSignificant single nucleotide polymorphismsGenome-wide dataGenetic Analysis Workshop 16 Problem 1 dataGenes/SNPsSNP markersSignificant SNPsSingle nucleotide polymorphismsGenetic association studiesWhole genomeChromosome 6Association studiesRheumatoid arthritis statusAntigen geneTraitsSNPsForestHLA-DRAArray experimentsGenomeMarkersHuman leukocyte antigen (HLA) genesGenesFurther analysisIndividual markersHigh levelsA genome-wide association analysis of Framingham Heart Study longitudinal data using multivariate adaptive splines
Zhu W, Cho K, Chen X, Zhang M, Wang M, Zhang H. A genome-wide association analysis of Framingham Heart Study longitudinal data using multivariate adaptive splines. BMC Proceedings 2009, 3: s119. PMID: 20017984, PMCID: PMC2795891, DOI: 10.1186/1753-6561-3-s7-s119.Peer-Reviewed Original ResearchTraits of interestGenome-wide analysisGenome-wide association studiesWide association analysisGenome-wide dataMultivariate adaptive splinesAssociation studiesAssociation analysisGene-environment interactionsTraitsLongitudinal phenotypesGene-environment interaction effectsMasalFramingham Heart StudyPermutation testGenesPhenotype