SCZ - Brain Cerebellar Hemisphere

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Last updated: 2022-02-27

Checks: 6 1

Knit directory: cTWAS_analysis/

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absolute	relative
/project2/xinhe/shengqian/cTWAS/cTWAS_analysis/data/	data
/project2/xinhe/shengqian/cTWAS/cTWAS_analysis/code/ctwas_config.R	code/ctwas_config.R

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File	Version	Author	Date	Message
Rmd	1c69dd2	sq-96	2022-02-27	update
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Weight QC

#number of imputed weights
nrow(qclist_all)

[1] 11359

#number of imputed weights by chromosome
table(qclist_all$chr)

   1    2    3    4    5    6    7    8    9   10   11   12   13   14   15   16 
1087  778  650  422  552  565  566  427  449  455  705  643  215  384  374  548 
  17   18   19   20   21   22 
 712  170  889  335  135  298 

#number of imputed weights without missing variants
sum(qclist_all$nmiss==0)

[1] 8808

#proportion of imputed weights without missing variants
mean(qclist_all$nmiss==0)

[1] 0.7754

Check convergence of parameters

Past versions of unnamed-chunk-5-1.png

Version	Author	Date
ff6403a	sq-96	2022-02-27

#estimated group prior
estimated_group_prior <- group_prior_rec[,ncol(group_prior_rec)]
names(estimated_group_prior) <- c("gene", "snp")
estimated_group_prior["snp"] <- estimated_group_prior["snp"]*thin #adjust parameter to account for thin argument
print(estimated_group_prior)

     gene       snp 
0.0166240 0.0002413 

#estimated group prior variance
estimated_group_prior_var <- group_prior_var_rec[,ncol(group_prior_var_rec)]
names(estimated_group_prior_var) <- c("gene", "snp")
print(estimated_group_prior_var)

 gene   snp 
9.241 8.684 

#report sample size
print(sample_size)

[1] 82315

#report group size
group_size <- c(nrow(ctwas_gene_res), n_snps)
print(group_size)

[1]   11359 7573890

#estimated group PVE
estimated_group_pve <- estimated_group_prior_var*estimated_group_prior*group_size/sample_size #check PVE calculation
names(estimated_group_pve) <- c("gene", "snp")
print(estimated_group_pve)

  gene    snp 
0.0212 0.1928 

#compare sum(PIP*mu2/sample_size) with above PVE calculation
c(sum(ctwas_gene_res$PVE),sum(ctwas_snp_res$PVE))

[1] 0.1128 1.4250

Genes with highest PIPs

Past versions of unnamed-chunk-7-1.png

Version	Author	Date
ff6403a	sq-96	2022-02-27

          genename region_tag susie_pip   mu2       PVE      z num_eqtl
10988       ZNF823      19_10    0.9863 29.29 0.0003509  5.479        2
4143         FEZF1       7_74    0.9829 27.95 0.0003338 -5.314        1
5783        GALNT2      1_117    0.9483 23.38 0.0002693  4.792        1
6241       ARFGAP2      11_29    0.9435 24.43 0.0002800  4.740        1
2207       RUNDC3B       7_54    0.9210 23.36 0.0002614  5.000        1
12095   AC012074.2       2_15    0.9201 21.31 0.0002382  4.623        1
13214 RP11-230C9.4      6_102    0.9113 19.95 0.0002208 -4.176        3
11339        DISP3        1_8    0.8673 19.04 0.0002006  3.889        2
3099         SF3B1      2_117    0.8640 42.46 0.0004457  6.725        1
9323        LPCAT4      15_10    0.7981 19.72 0.0001912 -4.171        2
5788        CEP170      1_128    0.7972 25.05 0.0002427 -5.138        2
1148          RRN3      16_15    0.7964 20.44 0.0001978 -4.236        1
13246  RP1-224A6.9       1_15    0.7939 19.69 0.0001899 -4.000        1
13014      TBC1D29      17_18    0.7747 21.67 0.0002040 -4.407        1
9372          LY6H       8_94    0.7666 20.46 0.0001906  4.074        1
3842        ABCC10       6_33    0.7560 22.93 0.0002106 -4.885        2
5459         RLBP1      15_41    0.7487 22.33 0.0002031 -4.224        1
11358        TCTN1      12_67    0.7370 24.35 0.0002180  4.840        1
174         ZNF207      17_19    0.7316 20.31 0.0001805  4.164        1
499        TRAPPC3       1_22    0.7257 24.20 0.0002133  4.907        1

Genes with largest effect sizes

Past versions of unnamed-chunk-8-1.png

Version	Author	Date
ff6403a	sq-96	2022-02-27

      genename region_tag susie_pip     mu2       PVE       z num_eqtl
3504     CRHR1      17_27 4.901e-01 3320.10 1.977e-02  3.3623        1
2449      WNT3      17_27 0.000e+00 2240.49 0.000e+00 -2.4566        1
12178 HLA-DQA2       6_26 2.229e-13  382.90 1.037e-15  0.3447        1
11553    CLIC1       6_26 1.674e-12  361.24 7.345e-15  8.8122        1
9601  HLA-DQB1       6_26 4.682e-13  359.75 2.046e-15  1.6253        2
11903   ARL17B      17_27 0.000e+00  351.12 0.000e+00 -3.0672        1
11078 HLA-DRB5       6_26 1.518e-13  300.99 5.549e-16  2.9680        1
10673 HLA-DRB1       6_26 1.292e-13  282.04 4.428e-16  2.4321        1
11298   HSPA1A       6_26 6.655e-13  226.53 1.831e-15  7.1259        1
9768     ACBD4      17_27 0.000e+00  176.90 0.000e+00  1.9129        3
12355      C4A       6_26 2.929e-12  153.42 5.460e-15  5.2909        1
10074  SPATA32      17_27 0.000e+00  142.76 0.000e+00 -0.5855        1
4955      NMT1      17_27 0.000e+00  139.79 0.000e+00  2.7209        1
10140    FMNL1      17_27 0.000e+00  132.09 0.000e+00  0.6638        1
10790 HLA-DQA1       6_26 1.145e-12  103.68 1.443e-15 -0.7786        1
11299   HSPA1L       6_26 2.491e-13   92.79 2.808e-16  0.9130        1
7012  ARHGAP27      17_27 0.000e+00   75.40 0.000e+00  1.0116        2
2458     GOSR2      17_27 0.000e+00   68.35 0.000e+00 -2.5096        1
4785     RINT1       7_65 0.000e+00   66.77 0.000e+00  1.1750        1
5086     PGBD1       6_22 2.321e-02   65.25 1.840e-05 -8.4933        1

Genes with highest PVE

          genename region_tag susie_pip     mu2       PVE      z num_eqtl
3504         CRHR1      17_27    0.4901 3320.10 0.0197678  3.362        1
3099         SF3B1      2_117    0.8640   42.46 0.0004457  6.725        1
10988       ZNF823      19_10    0.9863   29.29 0.0003509  5.479        2
4143         FEZF1       7_74    0.9829   27.95 0.0003338 -5.314        1
8510        INO80E      16_24    0.6459   38.23 0.0003000  6.350        1
6241       ARFGAP2      11_29    0.9435   24.43 0.0002800  4.740        1
5783        GALNT2      1_117    0.9483   23.38 0.0002693  4.792        1
2207       RUNDC3B       7_54    0.9210   23.36 0.0002614  5.000        1
5788        CEP170      1_128    0.7972   25.05 0.0002427 -5.138        2
12095   AC012074.2       2_15    0.9201   21.31 0.0002382  4.623        1
13214 RP11-230C9.4      6_102    0.9113   19.95 0.0002208 -4.176        3
11358        TCTN1      12_67    0.7370   24.35 0.0002180  4.840        1
499        TRAPPC3       1_22    0.7257   24.20 0.0002133  4.907        1
3842        ABCC10       6_33    0.7560   22.93 0.0002106 -4.885        2
13014      TBC1D29      17_18    0.7747   21.67 0.0002040 -4.407        1
5459         RLBP1      15_41    0.7487   22.33 0.0002031 -4.224        1
11339        DISP3        1_8    0.8673   19.04 0.0002006  3.889        2
9329        DIRAS1       19_3    0.7097   23.13 0.0001994 -4.658        1
1148          RRN3      16_15    0.7964   20.44 0.0001978 -4.236        1
4509         REEP2       5_82    0.7183   22.28 0.0001944  4.931        2

Genes with largest z scores

        genename region_tag susie_pip    mu2       PVE      z num_eqtl
10334     BTN3A2       6_20 2.898e-02  64.03 2.254e-05  9.098        2
11884      HCG11       6_20 3.007e-02  64.70 2.363e-05  9.082        1
12879 CTA-14H9.5       6_20 3.007e-02  64.70 2.363e-05  9.082        1
11553      CLIC1       6_26 1.674e-12 361.24 7.345e-15  8.812        1
2870      PRSS16       6_21 1.485e-01  60.49 1.091e-04 -8.567        1
5086       PGBD1       6_22 2.321e-02  65.25 1.840e-05 -8.493        1
6038        ABT1       6_20 6.328e-02  54.46 4.187e-05  8.156        1
2826      TRIM38       6_20 2.509e-02  46.56 1.419e-05 -7.765        2
6221       CNNM2      10_66 1.891e-01  35.94 8.256e-05 -7.691        1
11298     HSPA1A       6_26 6.655e-13 226.53 1.831e-15  7.126        1
7375        TYW5      2_118 6.863e-02  36.54 3.046e-05 -6.805        2
10488    ZSCAN23       6_22 1.296e-01  44.40 6.989e-05 -6.793        1
3099       SF3B1      2_117 8.640e-01  42.46 4.457e-04  6.725        1
1323     PITPNM2      12_75 3.200e-02  41.17 1.601e-05 -6.713        1
10845    ZSCAN26       6_22 2.575e-02  29.98 9.377e-06  6.660        2
2710      OGFOD2      12_75 1.707e-02  39.53 8.197e-06  6.579        1
9828     ARL6IP4      12_75 1.298e-02  38.31 6.044e-06 -6.491        1
8510      INO80E      16_24 6.459e-01  38.23 3.000e-04  6.350        1
10881     ZNF165       6_22 2.295e-02  26.72 7.449e-06  6.229        2
9199       ATG13      11_28 4.322e-01  35.28 1.852e-04 -6.169        1

Comparing z scores and PIPs

Past versions of unnamed-chunk-11-1.png

Version	Author	Date
ff6403a	sq-96	2022-02-27

Past versions of unnamed-chunk-11-2.png

Version	Author	Date
ff6403a	sq-96	2022-02-27

[1] 0.007307

        genename region_tag susie_pip    mu2       PVE      z num_eqtl
10334     BTN3A2       6_20 2.898e-02  64.03 2.254e-05  9.098        2
11884      HCG11       6_20 3.007e-02  64.70 2.363e-05  9.082        1
12879 CTA-14H9.5       6_20 3.007e-02  64.70 2.363e-05  9.082        1
11553      CLIC1       6_26 1.674e-12 361.24 7.345e-15  8.812        1
2870      PRSS16       6_21 1.485e-01  60.49 1.091e-04 -8.567        1
5086       PGBD1       6_22 2.321e-02  65.25 1.840e-05 -8.493        1
6038        ABT1       6_20 6.328e-02  54.46 4.187e-05  8.156        1
2826      TRIM38       6_20 2.509e-02  46.56 1.419e-05 -7.765        2
6221       CNNM2      10_66 1.891e-01  35.94 8.256e-05 -7.691        1
11298     HSPA1A       6_26 6.655e-13 226.53 1.831e-15  7.126        1
7375        TYW5      2_118 6.863e-02  36.54 3.046e-05 -6.805        2
10488    ZSCAN23       6_22 1.296e-01  44.40 6.989e-05 -6.793        1
3099       SF3B1      2_117 8.640e-01  42.46 4.457e-04  6.725        1
1323     PITPNM2      12_75 3.200e-02  41.17 1.601e-05 -6.713        1
10845    ZSCAN26       6_22 2.575e-02  29.98 9.377e-06  6.660        2
2710      OGFOD2      12_75 1.707e-02  39.53 8.197e-06  6.579        1
9828     ARL6IP4      12_75 1.298e-02  38.31 6.044e-06 -6.491        1
8510      INO80E      16_24 6.459e-01  38.23 3.000e-04  6.350        1
10881     ZNF165       6_22 2.295e-02  26.72 7.449e-06  6.229        2
9199       ATG13      11_28 4.322e-01  35.28 1.852e-04 -6.169        1

GO enrichment analysis for genes with PIP>0.5

#number of genes for gene set enrichment
length(genes)

[1] 41

Uploading data to Enrichr... Done.
  Querying GO_Biological_Process_2021... Done.
  Querying GO_Cellular_Component_2021... Done.
  Querying GO_Molecular_Function_2021... Done.
Parsing results... Done.
[1] "GO_Biological_Process_2021"

Past versions of unnamed-chunk-14-1.png

Version	Author	Date
ff6403a	sq-96	2022-02-27

[1] Term             Overlap          Adjusted.P.value Genes           
<0 rows> (or 0-length row.names)
[1] "GO_Cellular_Component_2021"

Past versions of unnamed-chunk-14-2.png

Version	Author	Date
ff6403a	sq-96	2022-02-27

[1] Term             Overlap          Adjusted.P.value Genes           
<0 rows> (or 0-length row.names)
[1] "GO_Molecular_Function_2021"

Past versions of unnamed-chunk-14-3.png

Version	Author	Date
ff6403a	sq-96	2022-02-27

[1] Term             Overlap          Adjusted.P.value Genes           
<0 rows> (or 0-length row.names)

DisGeNET enrichment analysis for genes with PIP>0.5

                                                 Description      FDR Ratio
13                                                   Measles 0.009839  1/14
44                           Schimke immunoosseous dysplasia 0.009839  1/14
50                           Newfoundland Rod-Cone Dystrophy 0.009839  1/14
51                                 Bothnia Retinal Dystrophy 0.009839  1/14
52 Familial encephalopathy with neuroserpin inclusion bodies 0.009839  1/14
54 HEMOLYTIC UREMIC SYNDROME, ATYPICAL, SUSCEPTIBILITY TO, 2 0.009839  1/14
55              ALPHA-KETOGLUTARATE DEHYDROGENASE DEFICIENCY 0.009839  1/14
57                                       JOUBERT SYNDROME 13 0.009839  1/14
65                SPASTIC PARAPLEGIA 72, AUTOSOMAL RECESSIVE 0.009839  1/14
66                 SPASTIC PARAPLEGIA 72, AUTOSOMAL DOMINANT 0.009839  1/14
   BgRatio
13  1/9703
44  1/9703
50  1/9703
51  1/9703
52  1/9703
54  1/9703
55  1/9703
57  1/9703
65  1/9703
66  1/9703

WebGestalt enrichment analysis for genes with PIP>0.5

Loading the functional categories...
Loading the ID list...
Loading the reference list...
Performing the enrichment analysis...

Warning in oraEnrichment(interestGeneList, referenceGeneList, geneSet, minNum =
minNum, : No significant gene set is identified based on FDR 0.05!

NULL

PIP Manhattan Plot

Warning: ggrepel: 2 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Past versions of unnamed-chunk-17-1.png

Version	Author	Date
ff6403a	sq-96	2022-02-27

Sensitivity, specificity and precision for silver standard genes

#number of genes in known annotations
print(length(known_annotations))

[1] 130

#number of genes in known annotations with imputed expression
print(sum(known_annotations %in% ctwas_gene_res$genename))

[1] 64

#significance threshold for TWAS
print(sig_thresh)

[1] 4.591

#number of ctwas genes
length(ctwas_genes)

[1] 9

#number of TWAS genes
length(twas_genes)

[1] 83

#show novel genes (ctwas genes with not in TWAS genes)
ctwas_gene_res[ctwas_gene_res$genename %in% novel_genes,report_cols]

          genename region_tag susie_pip   mu2       PVE      z num_eqtl
11339        DISP3        1_8    0.8673 19.04 0.0002006  3.889        2
13214 RP11-230C9.4      6_102    0.9113 19.95 0.0002208 -4.176        3

#sensitivity / recall
print(sensitivity)

  ctwas    TWAS 
0.01538 0.06923 

#specificity
print(specificity)

 ctwas   TWAS 
0.9994 0.9934 

#precision / PPV
print(precision)

 ctwas   TWAS 
0.2222 0.1084 

Past versions of unnamed-chunk-20-1.png

Version	Author	Date
ff6403a	sq-96	2022-02-27

Session information

sessionInfo()

R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)

Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.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_1.3.1      forcats_0.5.1     stringr_1.4.0     dplyr_1.0.7      
 [5] purrr_0.3.4       readr_2.1.1       tidyr_1.1.4       tidyverse_1.3.1  
 [9] tibble_3.1.6      WebGestaltR_0.4.4 disgenet2r_0.99.2 enrichR_3.0      
[13] cowplot_1.0.0     ggplot2_3.3.5     workflowr_1.6.2  

loaded via a namespace (and not attached):
 [1] fs_1.5.2          lubridate_1.8.0   bit64_4.0.5       doParallel_1.0.17
 [5] httr_1.4.2        rprojroot_2.0.2   tools_3.6.1       backports_1.4.1  
 [9] doRNG_1.8.2       utf8_1.2.2        R6_2.5.1          vipor_0.4.5      
[13] DBI_1.1.2         colorspace_2.0-2  withr_2.4.3       ggrastr_1.0.1    
[17] tidyselect_1.1.1  bit_4.0.4         curl_4.3.2        compiler_3.6.1   
[21] git2r_0.26.1      rvest_1.0.2       cli_3.1.0         Cairo_1.5-12.2   
[25] xml2_1.3.3        labeling_0.4.2    scales_1.1.1      apcluster_1.4.8  
[29] digest_0.6.29     rmarkdown_2.11    svglite_1.2.2     pkgconfig_2.0.3  
[33] htmltools_0.5.2   dbplyr_2.1.1      fastmap_1.1.0     highr_0.9        
[37] rlang_1.0.1       rstudioapi_0.13   RSQLite_2.2.8     jquerylib_0.1.4  
[41] farver_2.1.0      generics_0.1.1    jsonlite_1.7.2    vroom_1.5.7      
[45] magrittr_2.0.2    Matrix_1.2-18     ggbeeswarm_0.6.0  Rcpp_1.0.8       
[49] munsell_0.5.0     fansi_1.0.2       gdtools_0.1.9     lifecycle_1.0.1  
[53] stringi_1.7.6     whisker_0.3-2     yaml_2.2.1        plyr_1.8.6       
[57] grid_3.6.1        blob_1.2.2        ggrepel_0.9.1     parallel_3.6.1   
[61] promises_1.0.1    crayon_1.5.0      lattice_0.20-38   haven_2.4.3      
[65] hms_1.1.1         knitr_1.36        pillar_1.6.4      igraph_1.2.10    
[69] rjson_0.2.20      rngtools_1.5.2    reshape2_1.4.4    codetools_0.2-16 
[73] reprex_2.0.1      glue_1.6.2        evaluate_0.14     data.table_1.14.2
[77] modelr_0.1.8      vctrs_0.3.8       tzdb_0.2.0        httpuv_1.5.1     
[81] foreach_1.5.2     cellranger_1.1.0  gtable_0.3.0      assertthat_0.2.1 
[85] cachem_1.0.6      xfun_0.29         broom_0.7.10      later_0.8.0      
[89] iterators_1.0.14  beeswarm_0.2.3    memoise_2.0.1     ellipsis_0.3.2