Last updated: 2023-08-16

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File Version Author Date Message
Rmd 08eaf44 Jing Gu 2023-08-16 run ctwas for multiple traits

Load ctwas results

# top 1 method
res <- impute_expr_z(z_snp, weight = weight, ld_R_dir = ld_R_dir,
                         method = NULL, outputdir = outputdir, outname = outname.e,
                         harmonize_z = T, harmonize_wgt = T, scale_by_ld_variance=F,
                         strand_ambig_action_z = "recover", 
                         recover_strand_ambig_wgt = T
# lasso/elastic-net method
res <- impute_expr_z(z_snp, weight = weight, ld_R_dir = ld_R_dir,
                         method = NULL, outputdir = outputdir, outname = outname.e,
                         harmonize_z = T, harmonize_wgt = T, scale_by_ld_variance=F,
                         strand_ambig_action_z = "none", 
                         recover_strand_ambig_wgt = F

GWAS: UK Biobank GWAS summary statistics - European individuals

Weights: FUSION weights using top1, lasso, or elastic-net models were converted into PredictDB format and were not needed to do scaling when running ctwas.

Check convergence of parameters

cTWAS analysis on m6A alone

[1] "Check convergence for the top1 model:"
[1] "Table of group size:"
    SNP    gene 
8713250     888 
                                SNP      gene
estimated_group_prior     2.367e-04  0.023546
estimated_group_prior_var 2.129e+01 20.092186
estimated_group_pve       1.256e-01  0.001201
attributable_group_pve    9.905e-01  0.009474
[1] "Check convergence for the lasso model:"
[1] "Table of group size:"
    SNP    gene 
8713250     912 
                                SNP      gene
estimated_group_prior     2.295e-04  0.030160
estimated_group_prior_var 2.061e+01 25.750541
estimated_group_pve       1.178e-01  0.002024
attributable_group_pve    9.831e-01  0.016891
$top1


$lasso

Joint analysis of expression, splicing and m6A

[1] "Check convergence for the top1 model when jointly analyzing expression, splicing and m6A:"
[1] "Table of group size before/after matching with UKBB SNPs:"
                          SNP      eQTL     sQTL   m6AQTL
prior_group_size    9.324e+06 2005.0000 2191.000 918.0000
group_size          8.713e+06 1928.0000 2123.000 888.0000
percent_of_overlaps 9.345e-01    0.9616    0.969   0.9673
                                SNP      eQTL      sQTL    m6AQTL
estimated_group_prior     2.259e-04  0.019133  0.013771  0.023062
estimated_group_prior_var 2.033e+01 21.099884 61.117674 17.148019
estimated_group_pve       1.144e-01  0.002225  0.005107  0.001004
attributable_group_pve    9.321e-01  0.018124  0.041608  0.008177
[1] "Check convergence for the lasso model when jointly analyzing expression, splicing and m6A:"
[1] "Table of group size before/after matching with UKBB SNPs:"
                          SNP      eQTL     sQTL   m6AQTL
prior_group_size    9.324e+06 2005.0000 2191.000 918.0000
group_size          8.713e+06 1998.0000 2180.000 912.0000
percent_of_overlaps 9.345e-01    0.9965    0.995   0.9935
                                SNP      eQTL      sQTL    m6AQTL
estimated_group_prior     2.012e-04  0.011316  0.010990  0.033067
estimated_group_prior_var 2.053e+01 20.406853 26.836349 23.920423
estimated_group_pve       1.029e-01  0.001319  0.001838  0.002062
attributable_group_pve    9.517e-01  0.012198  0.016998  0.019072
$top1


$lasso

cTWAS results for individual analysis with m6A

top1 model

   genename region_tag susie_pip       z
1      TAP2       6_27    0.9968 -17.170
2   RANGAP1      22_17    0.9947   8.459
3   ZKSCAN5       7_61    0.9854   5.773
4    HNRNPK       9_41    0.9243   8.162
5     ADCY7      16_27    0.9120   4.410
6      MDM2      12_42    0.9089   4.085
7   ZSCAN25       7_61    0.8941   6.713
8      EPC1      10_24    0.8858   4.362
9   LAMTOR4       7_61    0.8442   4.218
10    BAZ1B       7_47    0.8115   4.511
11  THEMIS2       1_19    0.8025   7.209
12    DDX55      12_75    0.7969   6.612
13    RFTN1       3_12    0.7752   3.751
14     BRF1      14_55    0.7621  -3.816
15     RAI1      17_15    0.7489  -8.341
16 SLC25A11       17_5    0.7008  -5.529
17     GIT1      17_18    0.6791  -4.508
18    RNGTT       6_60    0.6765   3.507
19    TAF6L      11_35    0.6663   3.607
20     SMG9      19_30    0.6262   7.203

Summing up PIPs for m6A peaks located in the same gene

Top m6A PIPs by genes

# A tibble: 21 × 2
   genename total_susie_pip
   <chr>              <dbl>
 1 TAP2               0.997
 2 RANGAP1            0.995
 3 ZKSCAN5            0.985
 4 HNRNPK             0.924
 5 ADCY7              0.912
 6 EPC1               0.911
 7 MDM2               0.909
 8 ZSCAN25            0.894
 9 LAMTOR4            0.871
10 BAZ1B              0.812
# ℹ 11 more rows

cTWAS results for joint analysis using a lasso model

Top m6A modification pip

Top expression/splicing/m6A units

For m6A or splicing QTLs, they are assigned to the nearest genes (m6A needs to be confirmed with Kevin).

Top SNPs or genes with PIP > 0.6

$eQTL
            genename susie_pip group region_tag
1888          KDELR2    0.9925  eQTL        7_9
1988            SBF1    0.8858  eQTL      22_24
1297           APH1B    0.7581  eQTL      15_29
854            MEGF9    0.7101  eQTL       9_63
701  ENSG00000182165    0.7046  eQTL       7_55
441  ENSG00000251022    0.6958  eQTL       4_56
656            GNA12    0.6501  eQTL        7_5
1878 ENSG00000153363    0.6303  eQTL      1_110
1813 ENSG00000272578    0.6242  eQTL       22_7

$m6AQTL
     genename susie_pip  group region_tag
5037     TAP2    0.9969 m6AQTL       6_27
5086  RANGAP1    0.9956 m6AQTL      22_17
5051  ZKSCAN5    0.9880 m6AQTL       7_61
5077    ADCY7    0.9298 m6AQTL      16_27
5067     MDM2    0.9254 m6AQTL      12_42
5052  ZSCAN25    0.9111 m6AQTL       7_61
5058     EPC1    0.9077 m6AQTL      10_24
5027  THEMIS2    0.8327 m6AQTL       1_19
5047    BAZ1B    0.8304 m6AQTL       7_47
5075     BRF1    0.7993 m6AQTL      14_55
5055  LAMTOR4    0.7843 m6AQTL       7_61
4821 SLC25A11    0.7750 m6AQTL       17_5
4923     GMIP    0.7634 m6AQTL      19_16
4443    RNGTT    0.7098 m6AQTL       6_60
5073    DDX55    0.6788 m6AQTL      12_75
4917   ADGRE2    0.6509 m6AQTL      19_12
4651    SENP1    0.6424 m6AQTL      12_31

$sQTL
     genename susie_pip group region_tag
4025    APH1A    0.9979  sQTL       1_75
4062    MYO1G    0.9646  sQTL       7_33
3946     DPM1    0.7669  sQTL      20_31
4165    NAA20    0.7480  sQTL      20_14
4042    CASP8    0.7046  sQTL      2_119
2296   RNF181    0.6692  sQTL       2_54
2360   EIF4E2    0.6470  sQTL      2_137
4091   ZDHHC6    0.6398  sQTL      10_70
3192     RELT    0.6082  sQTL      11_41

Top m6A modification pip

   genename region_tag susie_pip       z
1      TAP2       6_27    0.9969 -17.170
2   RANGAP1      22_17    0.9956   8.459
3   ZKSCAN5       7_61    0.9880   5.773
4     ADCY7      16_27    0.9298   4.410
5      MDM2      12_42    0.9254   4.085
6   ZSCAN25       7_61    0.9111   6.713
7      EPC1      10_24    0.9077   4.362
8   THEMIS2       1_19    0.8327   7.209
9     BAZ1B       7_47    0.8304   4.511
10     BRF1      14_55    0.7993  -3.816

Summing up PIPs for m6A peaks located in the same gene

Top 10 m6A PIPs by genes

# A tibble: 819 × 2
   genename total_susie_pip
   <chr>              <dbl>
 1 TAP2               0.997
 2 RANGAP1            0.996
 3 ZKSCAN5            0.988
 4 EPC1               0.939
 5 ADCY7              0.930
 6 MDM2               0.925
 7 ZSCAN25            0.911
 8 THEMIS2            0.833
 9 BAZ1B              0.830
10 LAMTOR4            0.814
# ℹ 809 more rows

Top splicing PIPs

                     peak_id genename       pos region_tag susie_pip       z
1   chr1:150240527-150241098    APH1A 150210120       1_75    0.9979   6.100
2     chr7:45009474-45009639    MYO1G  44925489       7_33    0.9646 -13.705
3    chr20:49557470-49557642     DPM1  49538693      20_31    0.7669   3.989
4    chr20:20007563-20013746    NAA20  19923000      20_14    0.7480  -4.543
5   chr2:202141827-202149539    CASP8 202143928      2_119    0.7046   9.369
6     chr2:85823772-85824227   RNF181  85818886       2_54    0.6692   5.200
7   chr2:233415454-233415880   EIF4E2 233417552      2_137    0.6470   4.427
8  chr10:114186117-114186976   ZDHHC6 114169664      10_70    0.6398  -3.927
9    chr11:73101966-73102189     RELT  73002434      11_41    0.6082   3.727
10  chr1:160250036-160250976    PEX19 160150130       1_81    0.5964   4.143

Summing up PIPs for spliced introns located in the same gene

Top 10 splicing PIPs by genes

# A tibble: 10 × 2
   genename total_susie_pip
   <chr>              <dbl>
 1 APH1A              0.998
 2 MYO1G              0.965
 3 CNN2               0.944
 4 ALDH3A2            0.874
 5 DPM1               0.806
 6 HNRNPK             0.784
 7 NAA20              0.748
 8 CASP8              0.705
 9 CD46               0.697
10 RNF181             0.684

Top genes by combined PIP

            genename combined_pip expression_pip splicing_pip m6A_pip
1518          HNRNPK        1.021      0.000e+00    0.7844982 0.23666
186            APH1A        0.998      0.000e+00    0.9979107 0.00000
2910            TAP2        0.997      0.000e+00    0.0000000 0.99695
2435         RANGAP1        0.996      0.000e+00    0.0000000 0.99559
1626          KDELR2        0.992      9.925e-01    0.0000000 0.00000
3317         ZKSCAN5        0.988      0.000e+00    0.0000000 0.98800
1957           MYO1G        0.965      0.000e+00    0.9645679 0.00000
567             CNN2        0.944      0.000e+00    0.9440766 0.00000
1239            EPC1        0.939      0.000e+00    0.0000000 0.93925
86             ADCY7        0.930      0.000e+00    0.0000000 0.92984
1792            MDM2        0.929      0.000e+00    0.0038008 0.92544
3397         ZSCAN25        0.911      0.000e+00    0.0000000 0.91106
2620            SBF1        0.886      8.858e-01    0.0000000 0.00000
133          ALDH3A2        0.874      0.000e+00    0.8736031 0.00000
1670         LAMTOR4        0.868      6.078e-03    0.0485338 0.81372
2962         THEMIS2        0.833      0.000e+00    0.0000000 0.83269
284            BAZ1B        0.830      0.000e+00    0.0000000 0.83038
1394            GMIP        0.815      0.000e+00    0.0516449 0.76338
756             DPM1        0.806      0.000e+00    0.8056706 0.00000
324             BRF1        0.799      0.000e+00    0.0000000 0.79935
2703        SLC25A11        0.775      0.000e+00    0.0000000 0.77499
187            APH1B        0.758      7.581e-01    0.0000000 0.00000
1962           NAA20        0.748      0.000e+00    0.7480051 0.00000
2758            SMG9        0.722      1.236e-01    0.0000000 0.59878
1396           GNA12        0.714      6.501e-01    0.0000000 0.06393
1810           MEGF9        0.710      7.101e-01    0.0000000 0.00000
2528           RNGTT        0.710      0.000e+00    0.0000000 0.70979
413            CASP8        0.705      0.000e+00    0.7046435 0.00000
876  ENSG00000182165        0.705      7.046e-01    0.0000000 0.00000
471             CD46        0.697      0.000e+00    0.6969764 0.00000
1887          MRPL14        0.697      1.192e-01    0.0000000 0.57744
1062 ENSG00000251022        0.696      6.958e-01    0.0000000 0.00000
2517          RNF181        0.684      0.000e+00    0.6838361 0.00000
694            DDX55        0.679      3.132e-05    0.0002274 0.67884
2481           RFTN1        0.660      0.000e+00    0.0922329 0.56765
90            ADGRE2        0.651      0.000e+00    0.0000000 0.65092
822           EIF4E2        0.647      0.000e+00    0.6470154 0.00000
2648           SENP1        0.642      5.940e-05    0.0000000 0.64241
3302          ZDHHC6        0.640      0.000e+00    0.6398440 0.00000
860  ENSG00000153363        0.630      6.303e-01    0.0000000 0.00000
     region_tag
1518       9_41
186        1_75
2910       6_27
2435      22_17
1626        7_9
3317       7_61
1957       7_33
567        19_2
1239      10_24
86        16_27
1792      12_42
3397       7_61
2620      22_24
133       17_16
1670       7_61
2962       1_19
284        7_47
1394      19_16
756       20_31
324       14_55
2703       17_5
187       15_29
1962      20_14
2758      19_30
1396        7_5
1810       9_63
2528       6_60
413       2_119
876        7_55
471       1_107
1887       6_34
1062       4_56
2517       2_54
694       12_75
2481       3_12
90        19_12
822       2_137
2648      12_31
3302      10_70
860       1_110
Loading required package: grid
Warning: replacing previous import 'utils::download.file' by
'restfulr::download.file' when loading 'rtracklayer'

Locus plots for specific examples

     genename combined_pip expression_pip splicing_pip m6A_pip region_tag
1509    HMGCR         0.06              0            0 0.06028       5_44


R version 4.2.0 (2022-04-22)
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         LC_TIME=C           
 [4] LC_COLLATE=C         LC_MONETARY=C        LC_MESSAGES=C       
 [7] LC_PAPER=C           LC_NAME=C            LC_ADDRESS=C        
[10] LC_TELEPHONE=C       LC_MEASUREMENT=C     LC_IDENTIFICATION=C 

attached base packages:
[1] grid      stats4    stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] biomaRt_2.52.0       Gviz_1.40.1          cowplot_1.1.1       
 [4] ggplot2_3.4.3        GenomicRanges_1.48.0 GenomeInfoDb_1.32.2 
 [7] IRanges_2.30.1       S4Vectors_0.34.0     BiocGenerics_0.42.0 
[10] ctwas_0.1.38         dplyr_1.1.2          workflowr_1.7.0     

loaded via a namespace (and not attached):
  [1] colorspace_2.1-0            deldir_1.0-6               
  [3] rjson_0.2.21                rprojroot_2.0.3            
  [5] biovizBase_1.44.0           htmlTable_2.4.0            
  [7] XVector_0.36.0              base64enc_0.1-3            
  [9] fs_1.6.3                    dichromat_2.0-0.1          
 [11] rstudioapi_0.15.0           farver_2.1.1               
 [13] bit64_4.0.5                 AnnotationDbi_1.58.0       
 [15] fansi_1.0.4                 xml2_1.3.3                 
 [17] codetools_0.2-18            logging_0.10-108           
 [19] cachem_1.0.8                knitr_1.39                 
 [21] Formula_1.2-4               jsonlite_1.8.7             
 [23] Rsamtools_2.12.0            cluster_2.1.3              
 [25] dbplyr_2.3.3                png_0.1-7                  
 [27] compiler_4.2.0              httr_1.4.6                 
 [29] backports_1.4.1             lazyeval_0.2.2             
 [31] Matrix_1.6-1                fastmap_1.1.1              
 [33] cli_3.6.1                   later_1.3.0                
 [35] htmltools_0.5.2             prettyunits_1.1.1          
 [37] tools_4.2.0                 gtable_0.3.3               
 [39] glue_1.6.2                  GenomeInfoDbData_1.2.8     
 [41] rappdirs_0.3.3              Rcpp_1.0.11                
 [43] Biobase_2.56.0              jquerylib_0.1.4            
 [45] vctrs_0.6.3                 Biostrings_2.64.0          
 [47] rtracklayer_1.56.0          iterators_1.0.14           
 [49] xfun_0.30                   stringr_1.5.0              
 [51] ps_1.7.0                    lifecycle_1.0.3            
 [53] ensembldb_2.20.2            restfulr_0.0.14            
 [55] XML_3.99-0.14               getPass_0.2-2              
 [57] zlibbioc_1.42.0             scales_1.2.1               
 [59] BSgenome_1.64.0             VariantAnnotation_1.42.1   
 [61] ProtGenerics_1.28.0         hms_1.1.3                  
 [63] promises_1.2.0.1            MatrixGenerics_1.8.0       
 [65] parallel_4.2.0              SummarizedExperiment_1.26.1
 [67] AnnotationFilter_1.20.0     RColorBrewer_1.1-3         
 [69] yaml_2.3.5                  curl_5.0.2                 
 [71] memoise_2.0.1               gridExtra_2.3              
 [73] sass_0.4.1                  rpart_4.1.16               
 [75] latticeExtra_0.6-30         stringi_1.7.12             
 [77] RSQLite_2.3.1               highr_0.9                  
 [79] BiocIO_1.6.0                foreach_1.5.2              
 [81] checkmate_2.1.0             GenomicFeatures_1.48.4     
 [83] filelock_1.0.2              BiocParallel_1.30.3        
 [85] rlang_1.1.1                 pkgconfig_2.0.3            
 [87] matrixStats_0.62.0          bitops_1.0-7               
 [89] evaluate_0.15               lattice_0.20-45            
 [91] htmlwidgets_1.5.4           GenomicAlignments_1.32.0   
 [93] labeling_0.4.2              bit_4.0.5                  
 [95] processx_3.8.0              tidyselect_1.2.0           
 [97] magrittr_2.0.3              R6_2.5.1                   
 [99] generics_0.1.3              Hmisc_5.1-0                
[101] DelayedArray_0.22.0         DBI_1.1.3                  
[103] pgenlibr_0.3.6              pillar_1.9.0               
[105] whisker_0.4                 foreign_0.8-82             
[107] withr_2.5.0                 KEGGREST_1.36.2            
[109] RCurl_1.98-1.7              nnet_7.3-17                
[111] tibble_3.2.1                crayon_1.5.2               
[113] interp_1.1-4                utf8_1.2.3                 
[115] BiocFileCache_2.4.0         rmarkdown_2.14             
[117] jpeg_0.1-10                 progress_1.2.2             
[119] data.table_1.14.8           blob_1.2.4                 
[121] callr_3.7.3                 git2r_0.30.1               
[123] digest_0.6.33               httpuv_1.6.5               
[125] munsell_0.5.0               bslib_0.3.1