Last updated: 2022-11-09
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Knit directory: meSuSie_Analysis/
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This is to reproduce the real data analysis result of fine-mapping TC across EUR and AFR ancestries in the manuscript. The processed data and manual annotations can be found at the data directory.
load("/net/fantasia/home/borang/Susie_Mult/website_material/real_data/TC_ARIC4.RData")
library(MESuSiE)
We’ll start with exploring the region by locuszoom plot.
Version | Author | Date |
---|---|---|
65fba54 | borangao | 2022-11-09 |
We can see that rs6601924 is the leading SNP in the UKBB, but no strong marginal associations in the African ancestry with maximum -log10(P-value) less than 4. This suggests there is European ancestry-specific causal variant within the region.
We’ll do the analysis by performing univariate fine-mapping method in
each ancestry.
Version | Author | Date |
---|---|---|
65fba54 | borangao | 2022-11-09 |
Univariate SuSiE detects signals in European ancestry, and no signal is found in African ancestry
We further check the performance of MESuSiE in the scenario with only ancestry-specific causal variant.
Version | Author | Date |
---|---|---|
65fba54 | borangao | 2022-11-09 |
Our proposed method MESuSiE detects the leading signal rs6601924 as European ancestry-specific signal, Paintor also detects the leading variant rs6601924 as signal, while can not distinguish detected signal as shared or ancestry-specific.
sessionInfo()
R version 4.2.2 (2022-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.6 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.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] grid stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] DescTools_0.99.45 gridExtra_2.3 VennDiagram_1.7.3
[4] futile.logger_1.4.3 ggpmisc_0.4.7 ggpp_0.4.4
[7] patchwork_1.1.1 tidyr_1.2.0 dplyr_1.0.9
[10] data.table_1.14.2 ggpubr_0.4.0 ggplot2_3.3.6
[13] MESuSiE_1.0 workflowr_1.7.0
loaded via a namespace (and not attached):
[1] fs_1.5.2 httr_1.4.3 rprojroot_2.0.3
[4] tools_4.2.2 backports_1.4.1 bslib_0.3.1
[7] utf8_1.2.2 R6_2.5.1 DBI_1.1.2
[10] colorspace_2.0-3 withr_2.5.0 tidyselect_1.1.2
[13] Exact_3.1 processx_3.8.0 compiler_4.2.2
[16] git2r_0.30.1 cli_3.4.1 quantreg_5.93
[19] formatR_1.12 SparseM_1.81 expm_0.999-6
[22] labeling_0.4.2 sass_0.4.1 scales_1.2.1
[25] mvtnorm_1.1-3 callr_3.7.3 proxy_0.4-27
[28] stringr_1.4.0 digest_0.6.30 rmarkdown_2.14
[31] pkgconfig_2.0.3 htmltools_0.5.2 highr_0.9
[34] fastmap_1.1.0 rlang_1.0.6 readxl_1.4.0
[37] rstudioapi_0.13 jquerylib_0.1.4 generics_0.1.2
[40] farver_2.1.1 jsonlite_1.8.3 car_3.0-13
[43] magrittr_2.0.3 Matrix_1.4-1 Rcpp_1.0.8.3
[46] munsell_0.5.0 fansi_1.0.3 abind_1.4-5
[49] lifecycle_1.0.3 stringi_1.7.6 whisker_0.4
[52] yaml_2.3.5 carData_3.0-5 MASS_7.3-57
[55] rootSolve_1.8.2.3 promises_1.2.0.1 lmom_2.8
[58] lattice_0.20-45 splines_4.2.2 knitr_1.39
[61] ps_1.7.2 pillar_1.8.1 boot_1.3-28
[64] gld_2.6.5 ggsignif_0.6.3 futile.options_1.0.1
[67] glue_1.6.2 evaluate_0.18 getPass_0.2-2
[70] lambda.r_1.2.4 vctrs_0.5.0 httpuv_1.6.5
[73] MatrixModels_0.5-0 cellranger_1.1.0 gtable_0.3.1
[76] purrr_0.3.4 assertthat_0.2.1 xfun_0.31
[79] broom_0.8.0 e1071_1.7-11 rstatix_0.7.0
[82] later_1.3.0 class_7.3-20 survival_3.3-1
[85] tibble_3.1.7 ellipsis_0.3.2