Last updated: 2022-05-30

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Knit directory: meSuSie_Analysis/

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Package Installation

Install meSuSie package maintained in github through the “devtools” package.

if(!require(devtools))
  install.packages(devtools)
devtools::install_github("borangao/meSuSie")

Input Data

meSuSie requires correlation matrix and summary statistics. Correlation matrices are stored in a list, with element of the list being the correlation matrix from each ancestry. The column name of the matrix is the name of the SNP, and the order of the SNP should be consistent with the order in summary statistics. Summary statistics are stored in a list with length of the number ancestry. Each element of the list is the summary statistics for the ancestry. The minimum requirement of the summary statistics require the information of SNP, Beta, Se, Z and N. The column names should be exactly match for meSuSie to run.

Data Loading and Run meSuSie Analysis

library(meSuSie)
data("R_mat_list") 
data("summary_stat_list")
test_meSuSie<-meSuSie_core(R_mat_list,summary_stat_list,L=10,residual_variance=NULL,prior_weights=NULL,optim_method ="optim",estimate_residual_variance =F,max_iter =100)
*************************************************************

  Multiple Ancestry Sum of Single Effect Model (meSuSie)          

   Visit http://www.xzlab.org/software.html For Update            

            (C) 2022 Boran Gao, Xiang Zhou                        

              GNU General Public License                          

*************************************************************
# Start data processing for sufficient statistics 
# Create meSuSie object 
# Start data analysis 

# Data analysis is done, and now generates result 

Potential causal SNPs with PIP > 0.5:  SNP7 SNP413 

Credible sets for effects: 
$cs
$cs$L1
[1] 413

$cs$L2
[1] 7


$purity
   min.abs.corr mean.abs.corr median.abs.corr
L1            1             1               1
L2            1             1               1

$cs_index
[1] 1 2

$coverage
[1] 1 1

$requested_coverage
[1] 0.95


 Use meSusie_plot_pip() for Mahattan and PIP Plot
# Total time used for the analysis: 0.13 mins

Visualization: Manhattan and PIP Plot

library(ggplot2)
meSusie_plot_pip(test_meSuSie,R_mat_list,summary_stat_list)


sessionInfo()
R version 4.2.0 (2022-04-22)
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] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] ggplot2_3.3.6   meSuSie_1.0     workflowr_1.7.0

loaded via a namespace (and not attached):
 [1] progress_1.2.2    tidyselect_1.1.2  xfun_0.31         bslib_0.3.1      
 [5] purrr_0.3.4       colorspace_2.0-3  vctrs_0.4.1       generics_0.1.2   
 [9] htmltools_0.5.2   yaml_2.3.5        utf8_1.2.2        rlang_1.0.2      
[13] jquerylib_0.1.4   later_1.3.0       pillar_1.7.0      withr_2.5.0      
[17] DBI_1.1.2         glue_1.6.2        lifecycle_1.0.1   stringr_1.4.0    
[21] munsell_0.5.0     gtable_0.3.0      evaluate_0.15     labeling_0.4.2   
[25] knitr_1.39        callr_3.7.0       fastmap_1.1.0     httpuv_1.6.5     
[29] ps_1.7.0          fansi_1.0.3       highr_0.9         Rcpp_1.0.8.3     
[33] promises_1.2.0.1  scales_1.2.0      jsonlite_1.8.0    farver_2.1.0     
[37] fs_1.5.2          hms_1.1.1         digest_0.6.29     stringi_1.7.6    
[41] processx_3.5.3    dplyr_1.0.9       getPass_0.2-2     cowplot_1.1.1    
[45] rprojroot_2.0.3   grid_4.2.0        cli_3.3.0         tools_4.2.0      
[49] magrittr_2.0.3    sass_0.4.1        tibble_3.1.7      crayon_1.5.1     
[53] whisker_0.4       pkgconfig_2.0.3   ellipsis_0.3.2    prettyunits_1.1.1
[57] assertthat_0.2.1  rmarkdown_2.14    httr_1.4.3        rstudioapi_0.13  
[61] R6_2.5.1          git2r_0.30.1      compiler_4.2.0