Seven Uncorrelated Tissues Simulation
shengqian
2023-12-30
Last updated: 2024-01-18
Checks: 6 1
Knit directory: multigroup_ctwas_analysis/
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A simulation of seven uncorrelated tissues is conducted to evaluate cTWAS performance (parameter estimation, PIP calibration …). Seven tissues used in this simulation are Liver, Lung, Whole_Blood, Adipose_Subcutaneous, Artery_Tibial, Heart_Left_Ventricle, Stomach. The first three tissues are set to be causal and the other four tissues are non-causal.
Adipose Lung Artery Stomach Heart Whole_Blood Liver
Adipose 1 0.8 0.780 0.753 0.674 0.435 0.632
Lung NA 1.0 0.709 0.814 0.670 0.535 0.706
Artery NA NA 1.000 0.710 0.664 0.423 0.594
Stomach NA NA NA 1.000 0.705 0.484 0.760
Heart NA NA NA NA 1.000 0.438 0.650
Whole_Blood NA NA NA NA NA 1.000 0.498
Liver NA NA NA NA NA NA 1.000Simulation 1: 3% PVE for Causal Tissues and 0% PVE for Non-causal Tissues.
Results using PIP Threshold
simutag n_causal n_detected_pip n_detected_pip_in_causal
1 1-1 212 28 23
2 1-2 233 28 23
3 1-3 215 31 28
4 1-4 208 20 18
5 1-5 250 18 17[1] 0.872Results using Combined PIP Threshold
simutag n_causal_combined n_detected_comb_pip n_detected_comb_pip_in_causal
1 1-1 211 48 44
2 1-2 232 45 40
3 1-3 215 48 41
4 1-4 205 39 36
5 1-5 249 38 37[1] 0.9082569Estimated Prior Inclusion Probability
Estimated PVE
Separate effect size parameters
Results using PIP Threshold
simutag n_causal n_detected_pip n_detected_pip_in_causal
1 1-1 212 26 22
2 1-2 233 28 23
3 1-3 215 31 28
4 1-4 208 20 19
5 1-5 250 20 18[1] 0.88Results using Combined PIP Threshold
simutag n_causal_combined n_detected_comb_pip n_detected_comb_pip_in_causal
1 1-1 211 47 43
2 1-2 232 45 39
3 1-3 215 48 41
4 1-4 205 38 35
5 1-5 249 40 39[1] 0.9036697
PIP Calibration Plot
| Version | Author | Date |
|---|---|---|
| 55ada4e | sq-96 | 2024-01-18 |
sessionInfo()R version 4.1.0 (2021-05-18)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.3.13-el7-x86_64/lib/libopenblas_haswellp-r0.3.13.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] plyr_1.8.8 ggpubr_0.6.0 plotrix_3.8-4 cowplot_1.1.1
[5] ggplot2_3.4.0 latex2exp_0.9.6 data.table_1.14.6 ctwas_0.1.40
[9] workflowr_1.7.0
loaded via a namespace (and not attached):
[1] Rcpp_1.0.9 lattice_0.20-44 tidyr_1.3.0 getPass_0.2-2
[5] ps_1.7.2 assertthat_0.2.1 rprojroot_2.0.3 digest_0.6.31
[9] foreach_1.5.2 utf8_1.2.2 R6_2.5.1 backports_1.2.1
[13] evaluate_0.19 highr_0.9 httr_1.4.4 pillar_1.8.1
[17] rlang_1.1.1 rstudioapi_0.14 car_3.1-1 whisker_0.4.1
[21] callr_3.7.3 jquerylib_0.1.4 Matrix_1.3-3 rmarkdown_2.19
[25] labeling_0.4.2 stringr_1.5.0 munsell_0.5.0 broom_1.0.2
[29] compiler_4.1.0 httpuv_1.6.7 xfun_0.35 pkgconfig_2.0.3
[33] htmltools_0.5.4 tidyselect_1.2.0 gridExtra_2.3 tibble_3.1.8
[37] logging_0.10-108 codetools_0.2-18 fansi_1.0.3 dplyr_1.0.10
[41] withr_2.5.0 later_1.3.0 grid_4.1.0 jsonlite_1.8.4
[45] gtable_0.3.1 lifecycle_1.0.3 DBI_1.1.3 git2r_0.30.1
[49] magrittr_2.0.3 scales_1.2.1 carData_3.0-4 cli_3.6.1
[53] stringi_1.7.8 cachem_1.0.6 farver_2.1.0 ggsignif_0.6.4
[57] fs_1.5.2 promises_1.2.0.1 pgenlibr_0.3.2 bslib_0.4.1
[61] vctrs_0.6.3 generics_0.1.3 iterators_1.0.14 tools_4.1.0
[65] glue_1.6.2 purrr_1.0.2 abind_1.4-5 processx_3.8.0
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[73] knitr_1.41 sass_0.4.4