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.
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.
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.
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
loaded via a namespace (and not attached):
[1] httr_1.4.3 sass_0.4.1 jsonlite_1.8.3
[4] splines_4.2.2 carData_3.0-5 bslib_0.3.1
[7] assertthat_0.2.1 expm_0.999-6 highr_0.9
[10] gld_2.6.5 lmom_2.8 cellranger_1.1.0
[13] yaml_2.3.5 pillar_1.8.1 backports_1.4.1
[16] lattice_0.20-45 quantreg_5.93 glue_1.6.2
[19] digest_0.6.30 promises_1.2.0.1 ggsignif_0.6.3
[22] colorspace_2.0-3 htmltools_0.5.2 httpuv_1.6.5
[25] Matrix_1.4-1 pkgconfig_2.0.3 broom_0.8.0
[28] SparseM_1.81 purrr_0.3.4 mvtnorm_1.1-3
[31] scales_1.2.1 rootSolve_1.8.2.3 later_1.3.0
[34] MatrixModels_0.5-0 git2r_0.30.1 tibble_3.1.7
[37] proxy_0.4-27 farver_2.1.1 generics_0.1.2
[40] car_3.0-13 ellipsis_0.3.2 withr_2.5.0
[43] cli_3.4.1 readxl_1.4.0 survival_3.3-1
[46] magrittr_2.0.3 evaluate_0.18 fs_1.5.2
[49] fansi_1.0.3 MASS_7.3-57 rstatix_0.7.0
[52] class_7.3-20 tools_4.2.2 formatR_1.12
[55] lifecycle_1.0.3 Exact_3.1 stringr_1.4.0
[58] munsell_0.5.0 lambda.r_1.2.4 compiler_4.2.2
[61] jquerylib_0.1.4 e1071_1.7-11 rlang_1.0.6
[64] rstudioapi_0.13 labeling_0.4.2 rmarkdown_2.14
[67] boot_1.3-28 gtable_0.3.1 abind_1.4-5
[70] DBI_1.1.2 R6_2.5.1 knitr_1.39
[73] fastmap_1.1.0 utf8_1.2.2 workflowr_1.7.0
[76] rprojroot_2.0.3 futile.options_1.0.1 stringi_1.7.6
[79] Rcpp_1.0.8.3 vctrs_0.5.0 tidyselect_1.1.2
[82] xfun_0.31