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File Version Author Date Message
Rmd 72d6af3 sq-96 2023-01-06 update
html 72d6af3 sq-96 2023-01-06 update 
analysis_id <- params$analysis_id
trait_id <- params$trait_id
weight <- params$weight

results_dir <- paste0("/project2/xinhe/shengqian/cTWAS/cTWAS_analysis/data/", trait_id, "/", weight)

source("/project2/xinhe/shengqian/cTWAS/cTWAS_analysis/code/ctwas_config_b38.R")
options(digits = 4)

Load ctwas results

Check convergence of parameters

Version Author Date
72d6af3 sq-96 2023-01-06 
           SNP          Liver Liver_Splicing 
     0.0001129      0.0092207      0.0077965 
           SNP          Liver Liver_Splicing 
         12.94          38.08          19.66 
[1] 58.71
[1] 343621
           SNP          Liver Liver_Splicing 
       8696600          11003          21610 
           SNP          Liver Liver_Splicing 
      0.036977       0.011243       0.009639 
[1] 0.05786
           SNP          Liver Liver_Splicing 
        0.6391         0.1943         0.1666 
INFO:numexpr.utils:Note: NumExpr detected 28 cores but "NUMEXPR_MAX_THREADS" not set, so enforcing safe limit of 8.
finish

Attaching package: 'dplyr'
The following objects are masked from 'package:stats':

    filter, lag
The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union
ctwas_gene_res <- readRDS(paste0(results_dir,"/",analysis_id,"_ctwas_gene_res.RDS"))

ctwas_gene_res_E <- readRDS("/project2/xinhe/shengqian/cTWAS/cTWAS_analysis/data/LDL/Liver/ctwas_gene_res.RDS")
ctwas_gene_res_E["group"] <- "Liver_Expression_only"
alpha <- 0.05
sig_thresh <- qnorm(1-(alpha/nrow(ctwas_gene_res_E)/2), lower=T)

#ctwas_gene_res_E <- ctwas_gene_res_E[,c("genename","group","region_tag","susie_pip","mu2","PVE","z")]
ctwas_gene_res_E <- ctwas_gene_res_E[,c("genename","susie_pip","z")]
colnames(ctwas_gene_res_E) <- c("genename","expression_only_pip","twas_z")

ctwas_gene_res_S <- readRDS("/project2/xinhe/shengqian/cTWAS/cTWAS_analysis/data/LDL_S/Liver/LDL_Liver_ctwas_gene_res.RDS")
ctwas_gene_res_S["group"] <- "Liver_Expression_only"
#ctwas_gene_res_S <- ctwas_gene_res_S[,c("genename","group","region_tag","susie_pip","mu2","PVE","z")]
ctwas_gene_res_S <- ctwas_gene_res_S[,c("genename","susie_pip")]
colnames(ctwas_gene_res_S) <- c("genename","splicing_only_pip")

Top gene+tissue pairs by PIP

       genename            group region_tag susie_pip     mu2       PVE       z
42511     PARP9   Liver_Splicing       3_76    1.0480   43.27 1.321e-04   6.409
28221        HP   Liver_Splicing      16_38    1.0432  281.65 8.772e-04  21.869
3303      LRCH4   Liver_Splicing       7_61    1.0307   32.50 9.946e-05   5.294
5493   SLC22A18   Liver_Splicing       11_2    1.0244   20.75 6.177e-05   4.096
20901    ERGIC3   Liver_Splicing      20_21    1.0111   53.36 1.474e-04  -7.267
534       ASGR1   Liver_Splicing       17_6    1.0107   87.79 2.610e-04   9.645
21100     ABCA8   Liver_Splicing      17_39    1.0070   29.06 8.367e-05  -4.775
3228       LDLR   Liver_Splicing       19_9    1.0000  754.29 2.195e-03  26.898
4433      PSRC1 Liver_Expression       1_67    1.0000 1649.76 4.801e-03 -41.687
2454    ST3GAL4 Liver_Expression      11_77    1.0000  170.25 4.955e-04  13.376
11327       HPR Liver_Expression      16_38    1.0000  179.27 5.217e-04 -17.963
3720     INSIG2 Liver_Expression       2_69    1.0000   67.87 1.975e-04  -8.983
5561      ABCG8 Liver_Expression       2_27    0.9989  309.08 8.985e-04 -20.294
5988      FADS1 Liver_Expression      11_34    0.9977  164.34 4.772e-04  12.926
233      NPC1L1 Liver_Expression       7_32    0.9948   87.59 2.536e-04 -10.762
7405      ABCA1 Liver_Expression       9_53    0.9942   69.88 2.022e-04   7.982
16241   CYP4F12   Liver_Splicing      19_13    0.9919   38.71 1.019e-04  -5.868
27731     HLA-B   Liver_Splicing       6_25    0.9876   77.43 2.197e-04   9.069
8523       TNKS Liver_Expression       8_12    0.9874   73.03 2.099e-04  11.039
1597       PLTP Liver_Expression      20_28    0.9874   62.11 1.785e-04  -5.732
1999      PRKD2 Liver_Expression      19_33    0.9863   33.27 9.550e-05   5.072
9365       GAS6 Liver_Expression      13_62    0.9849   70.41 2.018e-04  -8.924
3754      RRBP1 Liver_Expression      20_13    0.9821   32.15 9.189e-05   7.008
38511     NADK2   Liver_Splicing       5_24    0.9817   21.64 6.020e-05   4.321
48011       PXK   Liver_Splicing       3_40    0.9804   57.28 1.002e-04   6.852
7036      INHBB Liver_Expression       2_70    0.9747   73.68 2.090e-04  -8.519
11910      ACP6   Liver_Splicing       1_73    0.9659   20.51 5.467e-05   3.994
11257    CYP2A6 Liver_Expression      19_28    0.9655   30.63 8.606e-05   5.407
6090    CSNK1G3 Liver_Expression       5_75    0.9614   83.51 2.336e-04   9.116
3247       KDSR Liver_Expression      18_35    0.9570   24.48 6.817e-05  -4.526
2092        SP4 Liver_Expression       7_19    0.9542  101.34 2.814e-04  10.693
8571     STAT5B Liver_Expression      17_25    0.9493   30.62 8.458e-05   5.426
6387     TTC39B Liver_Expression       9_13    0.9457   23.11 6.361e-05  -4.334
3300   C10orf88 Liver_Expression      10_77    0.9401   36.63 1.002e-04  -6.788
6217       PELO Liver_Expression       5_31    0.9369   71.14 1.940e-04   8.288
3562     ACVR1C Liver_Expression       2_94    0.9367   25.79 7.029e-05  -4.687
30201     ITGAL   Liver_Splicing      16_24    0.9326   22.82 5.679e-05  -4.428
10612    TRIM39 Liver_Expression       6_25    0.9250   81.36 2.190e-04   8.840
6774       PKN3 Liver_Expression       9_66    0.9216   47.52 1.274e-04  -6.621
4702      DDX56 Liver_Expression       7_32    0.9191   56.43 1.509e-04   9.642
1009      GSK3B Liver_Expression       3_74    0.9016   36.14 9.482e-05   6.475
8853       FUT2 Liver_Expression      19_33    0.8999  103.99 2.724e-04 -11.927
3123     KIF13B   Liver_Splicing       8_28    0.8776   24.61 5.516e-05  -4.718
28210   ALDH1A2   Liver_Splicing      15_26    0.8719   65.78 1.376e-04  -7.783
5542      CNIH4 Liver_Expression      1_114    0.8710   40.73 1.033e-04   6.146
9046    KLHDC7A Liver_Expression       1_13    0.8675   21.75 5.490e-05   4.124
34401     MARC1   Liver_Splicing      1_112    0.8650   30.76 6.466e-05   5.955
60641     THOP1   Liver_Splicing       19_3    0.8548   28.40 5.660e-05   5.087
105410   CCDC57   Liver_Splicing      17_47    0.8511   21.67 4.055e-05  -4.344
43701      PHC1   Liver_Splicing       12_9    0.8414   36.88 7.599e-05   6.156
6097       ALLC Liver_Expression        2_2    0.8407   27.83 6.809e-05   4.919
9054    SPTY2D1 Liver_Expression      11_13    0.8399   32.99 8.065e-05  -5.557
8411       POP7 Liver_Expression       7_62    0.8373   41.96 1.022e-04  -5.845
65291    UGT1A1   Liver_Splicing      2_137    0.8245   32.66 6.218e-05   5.450
6953       USP1 Liver_Expression       1_39    0.8235  252.66 6.055e-04  16.258
23511     FLOT2   Liver_Splicing      17_17    0.8214   34.23 5.561e-05  -3.738
23451      FKRP   Liver_Splicing      19_33    0.8181   24.34 3.675e-05  -3.018
5741     SPRED2   Liver_Splicing       2_42    0.8078   31.42 4.753e-05  -4.438
40561     NR1I2   Liver_Splicing       3_74    0.8014   29.82 4.898e-05  -5.960
62021    TMEM57   Liver_Splicing       1_18    0.8008  102.18 1.905e-04 -10.599

Top genes by combined PIP

      genename combined_pip expression_pip splicing_pip expression_only_pip
2779     DDX56       1.4552          0.919        0.536               0.947
2225     CNIH4       1.2616          0.871        0.391               0.978
8085       PXK       1.2172          0.237        0.980               0.793
9806   ST3GAL4       1.0781          1.000        0.078                  NA
7134     PARP9       1.0757          0.028        1.048               0.008
4661        HP       1.0432          0.000        1.043                  NA
5559     LRCH4       1.0331          0.002        1.031               0.007
158       ACP6       1.0327          0.067        0.966               0.798
6778    NPC1L1       1.0311          0.995        0.036               0.953
21       ABCA1       1.0302          0.994        0.036               0.995
9256  SLC22A18       1.0244          0.000        1.024                  NA
8746     RRBP1       1.0157          0.982        0.034               0.004
4668       HPR       1.0127          1.000        0.013               1.000
3375    ERGIC3       1.0111          0.000        1.011                  NA
813      ASGR1       1.0107          0.000        1.011                  NA
10912   TTC39B       1.0096          0.946        0.064               0.936
27       ABCA8       1.0070          0.000        1.007                  NA
2650   CYP4F12       1.0059          0.014        0.992               0.011
4015      GAS6       1.0012          0.985        0.016               0.988
7874     PRKD2       1.0004          0.986        0.014               0.986
5415      LDLR       1.0000          0.000        1.000                  NA
8001     PSRC1       1.0000          1.000        0.000               1.000
4911    INSIG2       1.0000          1.000        0.000               1.000
54       ABCG8       0.9989          0.999        0.000               1.000
3500     FADS1       0.9977          0.998        0.000               1.000
6470     NADK2       0.9945          0.013        0.982               0.019
7586      PLTP       0.9940          0.987        0.007               0.988
10447  TMEM199       0.9896          0.548        0.442               0.505
4583     HLA-B       0.9876          0.000        0.988               0.002
10610     TNKS       0.9874          0.987        0.000               0.991
10261    THOP1       0.9778          0.123        0.855               0.426
4893     INHBB       0.9747          0.975        0.000               0.982
12050  ZSCAN31       0.9740          0.421        0.553               0.348
2480   CSNK1G3       0.9706          0.961        0.010               0.975
5150      KDSR       0.9671          0.957        0.010               0.955
2627    CYP2A6       0.9655          0.965        0.000               0.962
9636       SP4       0.9542          0.954        0.000               0.977
9842    STAT5B       0.9493          0.949        0.000               0.926
1217  C10orf88       0.9401          0.940        0.000               0.932
7299      PELO       0.9369          0.937        0.000               0.935
197     ACVR1C       0.9367          0.937        0.000               0.923
11188    USP53       0.9362          0.152        0.784               0.521
4988     ITGAL       0.9326          0.000        0.933                  NA
10767   TRIM39       0.9250          0.925        0.000               0.999
1037     BCAT2       0.9218          0.135        0.787               0.547
7485      PKN3       0.9216          0.922        0.000               0.936
9772      SRRT       0.9170          0.786        0.131               0.934
451       ALLC       0.9140          0.841        0.073               0.793
4357     GSK3B       0.9016          0.902        0.000               0.673
3946      FUT2       0.8999          0.900        0.000               0.966
1160      BRI3       0.8937          0.733        0.161               0.734
5805     MARC1       0.8789          0.014        0.865               0.008
5197    KIF13B       0.8776          0.000        0.878                  NA
7366      PHC1       0.8726          0.031        0.842               0.021
413    ALDH1A2       0.8719          0.000        0.872                  NA
5249   KLHDC7A       0.8675          0.868        0.000               0.816
1664    CCDC57       0.8670          0.016        0.851               0.015
10517   TMEM57       0.8572          0.056        0.801               0.355
7436    PIH1D1       0.8528          0.111        0.742               0.365
11081   UGT1A1       0.8460          0.021        0.825               0.018
9736   SPTY2D1       0.8399          0.840        0.000               0.808
7696      POP7       0.8373          0.837        0.000               0.809
2552      CTSH       0.8315          0.639        0.193               0.556
11152     USP1       0.8235          0.823        0.000               0.895
3850     FLOT2       0.8214          0.000        0.821                  NA
3839      FKRP       0.8205          0.002        0.819               0.008
9714    SPRED2       0.8146          0.007        0.808               0.007
7809    PPP6R2       0.8134          0.022        0.791               0.029
6811     NR1I2       0.8126          0.011        0.802               0.009
10008    SYTL1       0.8050          0.789        0.016               0.792
        twas_z splicing_only_pip
2779    9.6419             0.109
2225    6.1455             1.803
8085   -3.7920             1.281
9806        NA             1.024
7134   -0.9822             1.159
4661        NA             1.060
5559    2.2446             1.095
158     4.0601             1.161
6778  -10.7619             0.063
21      7.9820             0.076
9256        NA             1.199
8746    2.5608             0.056
4668  -17.9628             0.026
3375        NA             1.119
813         NA             1.034
10912  -4.3345             0.139
27          NA             1.051
2650   -0.5298             1.192
4015   -8.9237             0.200
7874    5.0722             0.509
5415        NA             1.000
8001  -41.6873                NA
4911   -8.9827                NA
54    -20.2940                NA
3500   12.9264                NA
6470    1.0804             1.016
7586   -5.7325             0.177
10447   6.0117             0.607
4583    0.3148             0.992
10610  11.0386                NA
10261   4.9057             1.091
4893   -8.5189                NA
12050   1.6961             0.791
2480    9.1163             0.019
5150   -4.5263             0.152
2627    5.4070                NA
9636   10.6932                NA
9842    5.4263                NA
1217   -6.7878                NA
7299    8.2884                NA
197    -4.6874                NA
11188  -4.5084             0.999
4988        NA             1.036
10767   8.8402             0.005
1037    4.7964             0.968
7485   -6.6206                NA
9772    5.4250             0.741
451     4.9191             0.222
4357    6.4748                NA
3946  -11.9271                NA
1160   -5.1401             0.770
5805    1.2931             0.086
5197        NA             0.948
7366   -0.8107             0.905
413         NA             0.844
5249    4.1242                NA
1664    0.4010             1.440
10517 -10.2642             0.519
7436   -3.8775             0.981
11081   2.6601             0.909
9736   -5.5571                NA
7696   -5.8453                NA
2552    3.7956             0.756
11152  16.2582                NA
3850        NA             1.019
3839    3.8959             1.701
9714    0.9017             1.025
7809   -3.0827             1.141
6811    1.8213             0.516
10008  -3.9629             0.051
library("readxl")

known_annotations <- read_xlsx("data/summary_known_genes_annotations.xlsx", sheet="LDL")
New names:
• `` -> `...4`
• `` -> `...5`
known_annotations <- unique(known_annotations$`Gene Symbol`)

unrelated_genes <- df_gene$genename[!(df_gene$genename %in% known_annotations)]

#number of genes in known annotations
print(length(known_annotations))
[1] 69
#number of genes in known annotations with imputed expression
print(sum(known_annotations %in% df_gene$genename))
[1] 60
#assign ctwas, TWAS, and bystander genes
ctwas_genes <- df_gene$genename[df_gene$combined_pip>1]
twas_genes <- ctwas_gene_res_E$genename[abs(ctwas_gene_res_E$twas_z)>sig_thresh]

#significance threshold for TWAS
print(sig_thresh)
[1] 4.583
#number of ctwas genes
length(ctwas_genes)
[1] 21
#number of twas genes
length(twas_genes)
[1] 221
#sensitivity / recall
sensitivity <- rep(NA,1)
names(sensitivity) <- c("ctwas")
sensitivity["ctwas"] <- sum(ctwas_genes %in% known_annotations)/length(known_annotations)
sensitivity["TWAS"] <- sum(twas_genes %in% known_annotations)/length(known_annotations)
sensitivity
  ctwas    TWAS 
0.04348 0.27536 
#specificity
specificity <- rep(NA,1)
names(specificity) <- c("ctwas")
specificity["ctwas"] <- sum(!(unrelated_genes %in% ctwas_genes))/length(unrelated_genes)
specificity["TWAS"] <- sum(!(unrelated_genes %in% twas_genes))/length(unrelated_genes)
specificity
 ctwas   TWAS 
0.9985 0.9839 
#precision / PPV
precision <- rep(NA,1)
names(precision) <- c("ctwas")
precision["ctwas"] <- sum(ctwas_genes %in% known_annotations)/length(ctwas_genes)
precision["TWAS"] <- sum(twas_genes %in% known_annotations)/length(twas_genes)
precision
  ctwas    TWAS 
0.14286 0.08597 
#ROC curves

pip_range <- (0:1000)/1000
sensitivity <- rep(NA, length(pip_range))
specificity <- rep(NA, length(pip_range))

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] readxl_1.4.1    dplyr_1.0.10    reticulate_1.26 cowplot_1.1.1  
[5] ggplot2_3.4.0   workflowr_1.7.0

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.9        here_1.0.1        lattice_0.20-44   getPass_0.2-2    
 [5] png_0.1-8         ps_1.7.2          assertthat_0.2.1  rprojroot_2.0.3  
 [9] digest_0.6.31     utf8_1.2.2        R6_2.5.1          cellranger_1.1.0 
[13] RSQLite_2.2.19    evaluate_0.19     httr_1.4.4        highr_0.9        
[17] pillar_1.8.1      rlang_1.0.6       rstudioapi_0.14   data.table_1.14.6
[21] whisker_0.4.1     callr_3.7.3       jquerylib_0.1.4   blob_1.2.3       
[25] Matrix_1.3-3      rmarkdown_2.19    labeling_0.4.2    stringr_1.5.0    
[29] bit_4.0.5         munsell_0.5.0     compiler_4.1.0    httpuv_1.6.7     
[33] xfun_0.35         pkgconfig_2.0.3   htmltools_0.5.4   tidyselect_1.2.0 
[37] tibble_3.1.8      fansi_1.0.3       withr_2.5.0       later_1.3.0      
[41] grid_4.1.0        jsonlite_1.8.4    gtable_0.3.1      lifecycle_1.0.3  
[45] DBI_1.1.3         git2r_0.30.1      magrittr_2.0.3    scales_1.2.1     
[49] cli_3.4.1         stringi_1.7.8     cachem_1.0.6      farver_2.1.0     
[53] fs_1.5.2          promises_1.2.0.1  bslib_0.4.1       vctrs_0.5.1      
[57] generics_0.1.3    tools_4.1.0       bit64_4.0.5       glue_1.6.2       
[61] processx_3.8.0    fastmap_1.1.0     yaml_2.3.6        colorspace_2.0-3 
[65] memoise_2.0.1     knitr_1.41        sass_0.4.4