Last updated: 2023-08-22

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Knit directory: m6A_in_disease_genetics/

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File Version Author Date Message
Rmd 688d15c Jing Gu 2023-08-22 immune 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

Joint analysis of expression, splicing and m6A

[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     1.965e-04  0.005196  0.015474  0.020449
estimated_group_prior_var 3.621e+01 52.195130 31.455925 48.887256
estimated_group_pve       1.769e-01  0.001546  0.003028  0.002601
attributable_group_pve    9.610e-01  0.008398  0.016445  0.014130
$lasso

cTWAS results for individual analysis with m6A

top1 model

Summing up PIPs for m6A peaks located in the same gene

Top m6A PIPs by genes

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
1967   ZNF132    0.9859  eQTL      19_39
1806   MMACHC    0.9699  eQTL       1_29
1954   DNASE2    0.7971  eQTL      19_10
979     TRIM5    0.7582  eQTL       11_4
1831   WRNIP1    0.6198  eQTL        6_3

$m6AQTL
     genename susie_pip  group region_tag
5051 C17orf62    0.9632 m6AQTL      17_47
5021 SLC25A11    0.9579 m6AQTL       17_5
5088   UBE2G2    0.9184 m6AQTL      21_23
4984  THEMIS2    0.9180 m6AQTL       1_19
5008    TRAF2    0.8983 m6AQTL       9_74
5043    TAOK1    0.8696 m6AQTL      17_18
5019    PHF11    0.8610 m6AQTL      13_21
5075    AKAP8    0.8485 m6AQTL      19_12
5003  ZSCAN25    0.8295 m6AQTL       7_61
4993   PLXNA1    0.7925 m6AQTL       3_79
4534    GSDMD    0.7594 m6AQTL       8_94
5009    QSER1    0.6970 m6AQTL      11_22
4617    CD151    0.6313 m6AQTL       11_1
4995     AFF1    0.6087 m6AQTL       4_59

$sQTL
     genename susie_pip group region_tag
4173   ABHD12    0.9999  sQTL      20_19
4113    TOP3A    0.9998  sQTL      17_15
4004     ATIC    0.8582  sQTL      2_127
4017   FYTTD1    0.8315  sQTL      3_122
2406     USP4    0.7884  sQTL       3_35
3609    CWC25    0.7309  sQTL      17_23
3050  CWF19L1    0.7192  sQTL      10_64
2486   OCIAD2    0.6824  sQTL       4_38
4011    GSK3B    0.6606  sQTL       3_74
3617    HDAC5    0.6494  sQTL      17_26
2992    RPL12    0.6465  sQTL       9_66
3111    SAAL1    0.6340  sQTL      11_13

Top m6A modification pip

   genename region_tag susie_pip       z
1  C17orf62      17_47    0.9632   5.066
2  SLC25A11       17_5    0.9579 -15.751
3    UBE2G2      21_23    0.9184  -4.584
4   THEMIS2       1_19    0.9180   8.682
5     TRAF2       9_74    0.8983  -4.373
6     TAOK1      17_18    0.8696 -29.517
7     PHF11      13_21    0.8610  -5.372
8     AKAP8      19_12    0.8485  -5.185
9   ZSCAN25       7_61    0.8295  -5.164
10   PLXNA1       3_79    0.7925  -5.597

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 C17orf62           0.963
 2 SLC25A11           0.958
 3 UBE2G2             0.918
 4 THEMIS2            0.918
 5 TRAF2              0.898
 6 TAOK1              0.870
 7 PHF11              0.861
 8 AKAP8              0.849
 9 ZSCAN25            0.829
10 GSDMD              0.818
# ℹ 809 more rows

Top splicing PIPs

                     peak_id genename       pos region_tag susie_pip      z
1    chr20:25275666-25282855   ABHD12  25260931      20_19    0.9999  5.559
2    chr17:18188834-18193814    TOP3A  18095978      17_15    0.9998 -6.421
3   chr2:216213972-216224011     ATIC 216116915      2_127    0.8582 -3.866
4   chr3:197495458-197495689   FYTTD1 197441584      3_122    0.8315  4.156
5     chr3:49339975-49348053     USP4  49255503       3_35    0.7884  4.115
6    chr17:36959114-36963018    CWC25  36957432      17_23    0.7309 -4.441
7  chr10:102012941-102013178  CWF19L1 101937969      10_64    0.7192 -5.782
8     chr4:48887582-48896023   OCIAD2  48843230       4_38    0.6824  5.587
9   chr3:119582452-119624602    GSK3B 119503971       3_74    0.6606  4.097
10   chr17:42162523-42163940    HDAC5  42083840      17_26    0.6494  5.985

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 HNRNPK                1.09 
 2 ABHD12                1.00 
 3 TOP3A                 1.00 
 4 MAN2C1                0.893
 5 ATIC                  0.887
 6 FYTTD1                0.832
 7 USP4                  0.788
 8 INO80B-WBP1           0.787
 9 OS9                   0.772
10 STYXL1                0.748

Top genes by combined PIP

        genename combined_pip expression_pip splicing_pip  m6A_pip region_tag
1518      HNRNPK        1.136      0.0000000    1.0874414 0.048709       9_41
3059       TOP3A        1.002      0.0003334    0.9998311 0.001439      17_15
14        ABHD12        1.000      0.0000000    0.9999456 0.000000      20_19
3323      ZNF132        0.986      0.9858564    0.0000000 0.000000      19_39
1863      MMACHC        0.970      0.9699293    0.0000000 0.000000       1_29
354     C17orf62        0.963      0.0000000    0.0000000 0.963176      17_47
2703    SLC25A11        0.958      0.0000000    0.0000000 0.957935       17_5
2962     THEMIS2        0.918      0.0000000    0.0000000 0.917981       1_19
3166      UBE2G2        0.918      0.0000000    0.0000000 0.918412      21_23
3074       TRAF2        0.898      0.0000000    0.0000000 0.898278       9_74
1757      MAN2C1        0.893      0.0000000    0.8925246 0.000000      15_35
239         ATIC        0.887      0.0000000    0.8868402 0.000000      2_127
2908       TAOK1        0.870      0.0000000    0.0000000 0.869561      17_18
2208       PHF11        0.862      0.0000000    0.0005345 0.861005      13_21
111        AKAP8        0.849      0.0000000    0.0000000 0.848503      19_12
1355      FYTTD1        0.832      0.0000000    0.8315149 0.000000      3_122
3095       TRIM5        0.832      0.7581670    0.0736236 0.000000       11_4
3397     ZSCAN25        0.829      0.0000000    0.0000000 0.829473       7_61
1437       GSDMD        0.823      0.0042699    0.0000000 0.818362       8_94
1581 INO80B-WBP1        0.804      0.0000000    0.7870720 0.017100       2_48
Loading required package: grid
Warning: replacing previous import 'utils::download.file' by
'restfulr::download.file' when loading 'rtracklayer'

Locus plots for specific examples


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_1.4.7                 
 [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