## ----mychunk1, cache=TRUE, eval=TRUE, hide=TRUE------------------------------- library(metaCCA) data( package = 'metaCCA' ) ## ----mychunkN, cache=TRUE, eval=TRUE, hide=TRUE------------------------------- # Number of individuals in study 1 print( N1 ) # Number of individuals in study 2 print( N2 ) ## ----mychunk2, cache=TRUE, eval=TRUE, hide=TRUE------------------------------- # Part of the S_XY data frame for study 1 print( head(S_XY_study1[,1:6]), digits = 3 ) ## ----mychunk3, cache=TRUE, eval=TRUE, hide=TRUE------------------------------- # Part of the S_XX data frame for study 1 print( head(S_XX_study1[,1:6]), digits = 3 ) ## ----mychunk4, cache=TRUE, eval=TRUE, hide=TRUE------------------------------- # Estimating phenotypic correlation structure of study 1 S_YY_study1 = estimateSyy( S_XY = S_XY_full_study1 ) # Estimating phenotypic correlation structure of study 2 S_YY_study2 = estimateSyy( S_XY = S_XY_full_study2 ) ## ----mychunk5, cache=TRUE, eval=TRUE, hide=TRUE------------------------------- print( head(S_YY_study1[,1:6]), digits = 3 ) ## ----mychunk6, cache=TRUE, eval=TRUE, hide=TRUE------------------------------- # Default single-SNP--multi-trait meta-analysis of 2 studies # Association analysis according to metaCCA algorithm metaCCA_res1 = metaCcaGp( nr_studies = 2, S_XY = list( S_XY_study1, S_XY_study2 ), std_info = c( 0, 0 ), S_YY = list( S_YY_study1, S_YY_study2 ), N = c( N1, N2) ) # Association analysis according to metaCCA+ algorithm metaCCApl_res1 = metaCcaPlusGp( nr_studies = 2, S_XY = list( S_XY_study1, S_XY_study2 ), std_info = c( 0, 0 ), S_YY = list( S_YY_study1, S_YY_study2 ), N = c( N1, N2 ) ) ## ----mychunk7, cache=TRUE, eval=TRUE, hide=TRUE------------------------------- # Result of metaCCA print( metaCCA_res1[1:2], digits = 2 ) print( metaCCA_res1[3], digits = 1 ) ## ----mychunk72, cache=TRUE, eval=TRUE, hide=TRUE------------------------------ # Result of metaCCA+ print( metaCCApl_res1[1:2], digits = 2 ) print( metaCCApl_res1[3], digits = 1 ) ## ----mychunk8, cache=TRUE, eval=TRUE, hide=TRUE------------------------------- # Single-SNP--multi-trait meta-analysis of 2 studies # and one selected SNP # metaCCA metaCCA_res2 = metaCcaGp( nr_studies = 2, S_XY = list( S_XY_study1, S_XY_study2 ), std_info = c( 0, 0 ), S_YY = list( S_YY_study1, S_YY_study2 ), N = c( N1, N2 ), analysis_type = 1, SNP_id = 'rs80' ) # Result of metaCCA print( metaCCA_res2, digits = 2 ) ## ----mychunk9, cache=TRUE, eval=TRUE, hide=TRUE------------------------------- # metaCCA+ metaCCApl_res2 = metaCcaPlusGp( nr_studies = 2, S_XY = list( S_XY_study1, S_XY_study2 ), std_info = c( 0, 0 ), S_YY = list( S_YY_study1, S_YY_study2 ), N = c( N1, N2 ), analysis_type = 1, SNP_id = 'rs80' ) # Result of metaCCA+ print( metaCCApl_res2, digits = 2 ) ## ----mychunk11, cache=TRUE, eval=TRUE, hide=TRUE------------------------------ # Multi-SNP--multi-trait meta-analysis of 2 studies # metaCCA metaCCA_res3 = metaCcaGp( nr_studies = 2, S_XY = list( S_XY_study1, S_XY_study2 ), std_info = c( 0, 0 ), S_YY = list( S_YY_study1, S_YY_study2 ), N = c( N1, N2 ), analysis_type = 2, SNP_id = c( 'rs10', 'rs80', 'rs140', 'rs170', 'rs172' ), S_XX = list( S_XX_study1, S_XX_study2 ) ) # Result of metaCCA print( metaCCA_res3[1:2], digits = 2 ) print( metaCCA_res3[3], digits = 2, row.names = FALSE ) print( metaCCA_res3[4], digits = 2, row.names = FALSE ) ## ----mychunk12, cache=TRUE, eval=TRUE, hide=TRUE------------------------------ # metaCCA+ metaCCApl_res3 = metaCcaPlusGp( nr_studies = 2, S_XY = list( S_XY_study1, S_XY_study2 ), std_info = c( 0, 0 ), S_YY = list( S_YY_study1, S_YY_study2 ), N = c( N1, N2 ), analysis_type = 2, SNP_id = c( 'rs10', 'rs80', 'rs140', 'rs170', 'rs172' ), S_XX = list( S_XX_study1, S_XX_study2 )) # Result of metaCCA+ print( metaCCApl_res3[1:2], digits = 2 ) print( metaCCApl_res3[3], digits = 1, row.names = FALSE ) print( metaCCApl_res3[4], digits = 1, row.names = FALSE ) ## ----mychunk13, cache=TRUE, eval=TRUE, hide=TRUE------------------------------ S_XX_common = S_XX_study1 ## ----mychunk14, cache=TRUE, eval=TRUE, hide=TRUE------------------------------ # metaCCA metaCCA_res4 = metaCcaGp( nr_studies = 2, S_XY = list( S_XY_study1, S_XY_study2 ), std_info = c( 0, 0 ), S_YY = list( S_YY_study1, S_YY_study2 ), N = c( N1, N2 ), analysis_type = 2, SNP_id = c( 'rs10', 'rs80', 'rs140', 'rs170', 'rs172' ), S_XX = list( S_XX_common, S_XX_common ) ) # Result of metaCCA print( metaCCA_res4[1:2], digits = 2 ) print( metaCCA_res4[3], digits = 2, row.names = FALSE ) print( metaCCA_res4[4], digits = 2, row.names = FALSE ) ## ----mychunk15, cache=TRUE, eval=TRUE, hide=TRUE------------------------------ # metaCCA+ metaCCApl_res4 = metaCcaPlusGp( nr_studies = 2, S_XY = list( S_XY_study1, S_XY_study2 ), std_info = c( 0, 0 ), S_YY = list( S_YY_study1, S_YY_study2 ), N = c( N1, N2 ), analysis_type = 2, SNP_id = c( 'rs10', 'rs80', 'rs140', 'rs170', 'rs172' ), S_XX = list( S_XX_common, S_XX_common )) # Result of metaCCA+ print( metaCCApl_res4[1:2], digits = 2 ) print( metaCCApl_res4[3], digits = 1, row.names = FALSE ) print( metaCCApl_res4[4], digits = 1, row.names = FALSE )