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Type 'q()' to quit R. > # This file is part of the standard setup for testthat. > # It is recommended that you do not modify it. > # > # Where should you do additional test configuration? > # Learn more about the roles of various files in: > # * https://r-pkgs.org/tests.html > # * https://testthat.r-lib.org/reference/test_package.html#special-files > > library(testthat) > library(comorbidPGS) Attaching package: 'comorbidPGS' The following object is masked from 'package:graphics': assocplot > > test_check("comorbidPGS") --- Association testing: PGS: ldl_PGS Phenotype: WRONG_PHENO Covariate: NA --- Association testing: PGS: ldl_PGS Phenotype: test Covariate: NA Phenotype type: Continuous `test` ~ `ldl_PGS` Using a Linear regression Sample Size: 10000 Beta ( SE ): 0.2825228 ( 0.01000075 ) P-value: 5.462199e-169 --- Association testing: PGS: ldl_PGS Phenotype: test2 Covariate: NA Phenotype type: Continuous `test2` ~ `ldl_PGS` Using a Linear regression Sample Size: 4000 Beta ( SE ): 0.2845385 ( 0.01581542 ) P-value: 1.191072e-69 --- Association testing: PGS: ldl_PGS Phenotype: WRONG_PHENO Covariate: NA --- Association testing: PGS: brc_PGS Phenotype: ethnicity Covariate: NA Phenotype type: Categorical `ethnicity` ~ `brc_PGS`# weights: 12 (6 variable) initial value 13862.943611 iter 10 value 9697.260945 final value 9696.463691 converged Using a Multinomial logistic regression Sample Size: 8523 7586 6653 OR [ 95% CI ]: 1.007334 1.028451 0.9348368 [ 0.9592139 0.9670665 0.8277834 - 1.057869 1.093732 1.055735 ] P-value: 0.7698207 0.3716085 0.27751 --- Association testing: PGS: brc_PGS Phenotype: brc Covariate: NA Phenotype type: Cases/Controls `brc` ~ `brc_PGS` Using a Binary logistic regression Cases: 402 Controls: 5041 Sample Size: 5443 OR [ 95% CI ]: 1.540077 [ 1.390127 - 1.706201 ] P-value: 1.425869e-16 --- Association testing: PGS: brc_PGS Phenotype: t2d Covariate: NA Phenotype type: Cases/Controls `t2d` ~ `brc_PGS` Using a Binary logistic regression Cases: 730 Controls: 9270 Sample Size: 10000 OR [ 95% CI ]: 1.065721 [ 0.988462 - 1.149018 ] P-value: 0.09736706 --- Association testing: PGS: brc_PGS Phenotype: log_ldl Covariate: NA Phenotype type: Continuous `log_ldl` ~ `brc_PGS` Using a Linear regression Sample Size: 10000 Beta ( SE ): 0.001319107 ( 0.002329391 ) P-value: 0.5712104 --- Association testing: PGS: brc_PGS Phenotype: sbp_cat Covariate: NA Phenotype type: Ordered Categorical `sbp_cat` ~ `brc_PGS` Using a Ordinal logistic regression Sample Size: 10000 OR [ 95% CI ]: 0.9885508 [ 0.9526072 - 1.025851 ] P-value: 0.5422738 --- Association testing: PGS: t2d_PGS Phenotype: ethnicity Covariate: NA Phenotype type: Categorical `ethnicity` ~ `t2d_PGS`# weights: 12 (6 variable) initial value 13862.943611 iter 10 value 9697.368074 final value 9696.630119 converged Using a Multinomial logistic regression Sample Size: 8523 7586 6653 OR [ 95% CI ]: 0.9816761 1.017569 0.944661 [ 0.9347786 0.9567993 0.8367048 - 1.030926 1.082199 1.066546 ] P-value: 0.4590068 0.5793326 0.3578543 --- Association testing: PGS: t2d_PGS Phenotype: brc Covariate: NA Phenotype type: Cases/Controls `brc` ~ `t2d_PGS` Using a Binary logistic regression Cases: 402 Controls: 5041 Sample Size: 5443 OR [ 95% CI ]: 0.9968246 [ 0.9005324 - 1.103413 ] P-value: 0.9510713 --- Association testing: PGS: t2d_PGS Phenotype: t2d Covariate: NA Phenotype type: Cases/Controls `t2d` ~ `t2d_PGS` Using a Binary logistic regression Cases: 730 Controls: 9270 Sample Size: 10000 OR [ 95% CI ]: 1.688258 [ 1.561821 - 1.824931 ] P-value: 1.059304e-39 --- Association testing: PGS: t2d_PGS Phenotype: log_ldl Covariate: NA Phenotype type: Continuous `log_ldl` ~ `t2d_PGS` Using a Linear regression Sample Size: 10000 Beta ( SE ): 0.004699851 ( 0.002328954 ) P-value: 0.04361698 --- Association testing: PGS: t2d_PGS Phenotype: sbp_cat Covariate: NA Phenotype type: Ordered Categorical `sbp_cat` ~ `t2d_PGS` Using a Ordinal logistic regression Sample Size: 10000 OR [ 95% CI ]: 1.043724 [ 1.005803 - 1.083074 ] P-value: 0.02342431 --- Association testing: PGS: ldl_PGS Phenotype: ethnicity Covariate: NA Phenotype type: Categorical `ethnicity` ~ `ldl_PGS`# weights: 12 (6 variable) initial value 13862.943611 iter 10 value 9699.063415 final value 9697.386957 converged Using a Multinomial logistic regression Sample Size: 8523 7586 6653 OR [ 95% CI ]: 0.9926441 1.008565 0.9760944 [ 0.9452463 0.9482935 0.8647736 - 1.042419 1.072667 1.101745 ] P-value: 0.7674098 0.7861848 0.6953251 --- Association testing: PGS: ldl_PGS Phenotype: brc Covariate: NA Phenotype type: Cases/Controls `brc` ~ `ldl_PGS` Using a Binary logistic regression Cases: 402 Controls: 5041 Sample Size: 5443 OR [ 95% CI ]: 1.102213 [ 0.9947429 - 1.221295 ] P-value: 0.06298496 --- Association testing: PGS: ldl_PGS Phenotype: t2d Covariate: NA Phenotype type: Cases/Controls `t2d` ~ `ldl_PGS` Using a Binary logistic regression Cases: 730 Controls: 9270 Sample Size: 10000 OR [ 95% CI ]: 0.9843712 [ 0.913016 - 1.061303 ] P-value: 0.6815914 --- Association testing: PGS: ldl_PGS Phenotype: log_ldl Covariate: NA Phenotype type: Continuous `log_ldl` ~ `ldl_PGS` Using a Linear regression Sample Size: 10000 Beta ( SE ): 0.08287867 ( 0.002176973 ) P-value: 2.794232e-296 --- Association testing: PGS: ldl_PGS Phenotype: sbp_cat Covariate: NA Phenotype type: Ordered Categorical `sbp_cat` ~ `ldl_PGS` Using a Ordinal logistic regression Sample Size: 10000 OR [ 95% CI ]: 1.009039 [ 0.9724275 - 1.047029 ] P-value: 0.6332175 ------ Multiple associations ( 4 ) testing: No parallelisation, this operation may be slower | | | 0% --- Association testing: PGS: brc_PGS Phenotype: ethnicity Covariate: NA Phenotype type: Categorical `ethnicity` ~ `brc_PGS`# weights: 12 (6 variable) initial value 13862.943611 iter 10 value 9697.260945 final value 9696.463691 converged Using a Multinomial logistic regression Sample Size: 8523 7586 6653 OR [ 95% CI ]: 1.007334 1.028451 0.9348368 [ 0.9592139 0.9670665 0.8277834 - 1.057869 1.093732 1.055735 ] P-value: 0.7698207 0.3716085 0.27751 | |================== | 25% --- Association testing: PGS: t2d_PGS Phenotype: t2d Covariate: NA Phenotype type: Cases/Controls `t2d` ~ `t2d_PGS` Using a Binary logistic regression Cases: 730 Controls: 9270 Sample Size: 10000 OR [ 95% CI ]: 1.688258 [ 1.561821 - 1.824931 ] P-value: 1.059304e-39 | |=================================== | 50% --- Association testing: PGS: ldl_PGS Phenotype: log_ldl Covariate: NA Phenotype type: Continuous `log_ldl` ~ `ldl_PGS` Using a Linear regression Sample Size: 10000 Beta ( SE ): 0.08287867 ( 0.002176973 ) P-value: 2.794232e-296 | |==================================================== | 75% --- Association testing: PGS: brc_PGS Phenotype: sbp_cat Covariate: NA Phenotype type: Ordered Categorical `sbp_cat` ~ `brc_PGS` Using a Ordinal logistic regression Sample Size: 10000 OR [ 95% CI ]: 0.9885508 [ 0.9526072 - 1.025851 ] P-value: 0.5422738 | |======================================================================| 100% ------ Multiple associations ( 1 ) testing: No parallelisation, this operation may be slower | | | 0% --- Association testing: PGS: ldl_PGS Phenotype: t2d Covariate: NA Phenotype type: Cases/Controls `t2d` ~ `ldl_PGS` Using a Binary logistic regression Cases: 730 Controls: 9270 Sample Size: 10000 OR [ 95% CI ]: 0.9843712 [ 0.913016 - 1.061303 ] P-value: 0.6815914 | |======================================================================| 100% ------ Multiple associations ( 4 ) testing: No parallelisation, this operation may be slower | | | 0% --- Association testing: PGS: brc_PGS Phenotype: ethnicity Covariate: age sex gen_array Phenotype type: Categorical `ethnicity` ~ `brc_PGS` + `age` + `sex` + `gen_array`# weights: 24 (15 variable) initial value 13862.943611 iter 10 value 9889.147974 iter 20 value 9695.268994 final value 9695.223614 converged Using a Multinomial logistic regression Sample Size: 8523 7586 6653 OR [ 95% CI ]: 1.007385 1.02833 0.9351081 [ 0.9592606 0.9669558 0.8280089 - 1.057924 1.0936 1.05606 ] P-value: 0.7682797 0.3735897 0.2796549 | |================== | 25% --- Association testing: PGS: t2d_PGS Phenotype: t2d Covariate: age sex gen_array Phenotype type: Cases/Controls `t2d` ~ `t2d_PGS` + `age` + `sex` + `gen_array` Using a Binary logistic regression Cases: 730 Controls: 9270 Sample Size: 10000 OR [ 95% CI ]: 1.735974 [ 1.602987 - 1.879994 ] P-value: 6.519559e-42 | |=================================== | 50% --- Association testing: PGS: ldl_PGS Phenotype: log_ldl Covariate: age sex gen_array Phenotype type: Continuous `log_ldl` ~ `ldl_PGS` + `age` + `sex` + `gen_array` Using a Linear regression Sample Size: 10000 Beta ( SE ): 0.08285451 ( 0.002118297 ) P-value: 1.682295e-311 | |==================================================== | 75% --- Association testing: PGS: brc_PGS Phenotype: sbp_cat Covariate: age sex gen_array Phenotype type: Ordered Categorical `sbp_cat` ~ `brc_PGS` + `age` + `sex` + `gen_array` Using a Ordinal logistic regression Sample Size: 10000 OR [ 95% CI ]: 0.9848488 [ 0.9485063 - 1.022584 ] P-value: 0.4261214 | |======================================================================| 100% ------ Multiple associations ( 4 ) testing: No parallelisation, this operation may be slower | | | 0% --- Association testing: PGS: brc_PGS Phenotype: ethnicity Covariate: age sex gen_array Phenotype type: Categorical `ethnicity` ~ `brc_PGS` + `age` + `sex` + `gen_array`# weights: 24 (15 variable) initial value 13862.943611 iter 10 value 9889.147974 iter 20 value 9695.268994 final value 9695.223614 converged Using a Multinomial logistic regression Sample Size: 8523 7586 6653 OR [ 95% CI ]: 1.007385 1.02833 0.9351081 [ 0.9592606 0.9669558 0.8280089 - 1.057924 1.0936 1.05606 ] P-value: 0.7682797 0.3735897 0.2796549 | |================== | 25% --- Association testing: PGS: t2d_PGS Phenotype: t2d Covariate: age sex gen_array Phenotype type: Cases/Controls `t2d` ~ `t2d_PGS` + `age` + `sex` + `gen_array` Using a Binary logistic regression Cases: 730 Controls: 9270 Sample Size: 10000 OR [ 95% CI ]: 1.735974 [ 1.602987 - 1.879994 ] P-value: 6.519559e-42 | |=================================== | 50% --- Association testing: PGS: ldl_PGS Phenotype: log_ldl Covariate: age sex gen_array Phenotype type: Continuous `log_ldl` ~ `ldl_PGS` + `age` + `sex` + `gen_array` Using a Linear regression Sample Size: 10000 Beta ( SE ): 0.08285451 ( 0.002118297 ) P-value: 1.682295e-311 | |==================================================== | 75% --- Association testing: PGS: brc_PGS Phenotype: sbp_cat Covariate: age sex gen_array Phenotype type: Ordered Categorical `sbp_cat` ~ `brc_PGS` + `age` + `sex` + `gen_array` Using a Ordinal logistic regression Sample Size: 10000 OR [ 95% CI ]: 0.9848488 [ 0.9485063 - 1.022584 ] P-value: 0.4261214 | |======================================================================| 100% ------ Multiple associations ( 4 ) testing: No parallelisation, this operation may be slower | | | 0% --- Association testing: PGS: brc_PGS Phenotype: ethnicity Covariate: age sex gen_array Phenotype type: Categorical `ethnicity` ~ `brc_PGS` + `age` + `sex` + `gen_array`# weights: 24 (15 variable) initial value 13862.943611 iter 10 value 9889.147974 iter 20 value 9695.268994 final value 9695.223614 converged Using a Multinomial logistic regression Sample Size: 8523 7586 6653 OR [ 95% CI ]: 1.007385 1.02833 0.9351081 [ 0.9592606 0.9669558 0.8280089 - 1.057924 1.0936 1.05606 ] P-value: 0.7682797 0.3735897 0.2796549 | |================== | 25% --- Association testing: PGS: t2d_PGS Phenotype: t2d Covariate: age sex gen_array Phenotype type: Cases/Controls `t2d` ~ `t2d_PGS` + `age` + `sex` + `gen_array` Using a Binary logistic regression Cases: 730 Controls: 9270 Sample Size: 10000 OR [ 95% CI ]: 1.735974 [ 1.602987 - 1.879994 ] P-value: 6.519559e-42 | |=================================== | 50% --- Association testing: PGS: ldl_PGS Phenotype: log_ldl Covariate: age sex gen_array Phenotype type: Continuous `log_ldl` ~ `ldl_PGS` + `age` + `sex` + `gen_array` Using a Linear regression Sample Size: 10000 Beta ( SE ): 0.08285451 ( 0.002118297 ) P-value: 1.682295e-311 | |==================================================== | 75% --- Association testing: PGS: brc_PGS Phenotype: sbp_cat Covariate: age sex gen_array Phenotype type: Ordered Categorical `sbp_cat` ~ `brc_PGS` + `age` + `sex` + `gen_array` Using a Ordinal logistic regression Sample Size: 10000 OR [ 95% CI ]: 0.9848488 [ 0.9485063 - 1.022584 ] P-value: 0.4261214 | |======================================================================| 100% ------ Multiple phenotypes associations ( 1 ) testing: | | | 0% --- Association testing: PGS: ldl_PGS Phenotype: brc Covariate: NA Phenotype type: Cases/Controls `brc` ~ `ldl_PGS` Using a Binary logistic regression Cases: 402 Controls: 5041 Sample Size: 5443 OR [ 95% CI ]: 1.102213 [ 0.9947429 - 1.221295 ] P-value: 0.06298496 | |======================================================================| 100% ------ Multiple phenotypes associations ( 5 ) testing: | | | 0% --- Association testing: PGS: brc_PGS Phenotype: ethnicity Covariate: age sex gen_array Phenotype type: Categorical `ethnicity` ~ `brc_PGS` + `age` + `sex` + `gen_array`# weights: 24 (15 variable) initial value 13862.943611 iter 10 value 9889.147974 iter 20 value 9695.268994 final value 9695.223614 converged Using a Multinomial logistic regression Sample Size: 8523 7586 6653 OR [ 95% CI ]: 1.007385 1.02833 0.9351081 [ 0.9592606 0.9669558 0.8280089 - 1.057924 1.0936 1.05606 ] P-value: 0.7682797 0.3735897 0.2796549 | |============== | 20% --- Association testing: PGS: brc_PGS Phenotype: brc Covariate: age sex gen_array Phenotype type: Cases/Controls `brc` ~ `brc_PGS` + `age` + `sex` + `gen_array` Using a Binary logistic regression Cases: 402 Controls: 5041 Sample Size: 5443 OR [ 95% CI ]: 1.547586 [ 1.395998 - 1.715634 ] P-value: 1.015466e-16 | |============================ | 40% --- Association testing: PGS: brc_PGS Phenotype: t2d Covariate: age sex gen_array Phenotype type: Cases/Controls `t2d` ~ `brc_PGS` + `age` + `sex` + `gen_array` Using a Binary logistic regression Cases: 730 Controls: 9270 Sample Size: 10000 OR [ 95% CI ]: 1.061921 [ 0.9840316 - 1.145976 ] P-value: 0.1221469 | |========================================== | 60% --- Association testing: PGS: brc_PGS Phenotype: log_ldl Covariate: age sex gen_array Phenotype type: Continuous `log_ldl` ~ `brc_PGS` + `age` + `sex` + `gen_array` Using a Linear regression Sample Size: 10000 Beta ( SE ): 0.0009742985 ( 0.002274659 ) P-value: 0.6684221 | |======================================================== | 80% --- Association testing: PGS: brc_PGS Phenotype: sbp_cat Covariate: age sex gen_array Phenotype type: Ordered Categorical `sbp_cat` ~ `brc_PGS` + `age` + `sex` + `gen_array` Using a Ordinal logistic regression Sample Size: 10000 OR [ 95% CI ]: 0.9848488 [ 0.9485063 - 1.022584 ] P-value: 0.4261214 | |======================================================================| 100% [ FAIL 0 | WARN 19 | SKIP 0 | PASS 106 ] [ FAIL 0 | WARN 19 | SKIP 0 | PASS 106 ] > > proc.time() user system elapsed 16.73 1.03 17.70