SCZ 2018 - Brain_Hippocampus

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Last updated: 2022-05-19

Checks: 5 2

Knit directory: cTWAS_analysis/

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library(reticulate)
use_python("/scratch/midway2/shengqian/miniconda3/envs/PythonForR/bin/python",required=T)

Weight QC

#number of imputed weights
nrow(qclist_all)

[1] 17848

#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 
1685 1258 1054  701  707  931 1057  622  737  814 1072  981  359  635  616  686 
  17   18   19   20   21   22 
1225  243 1275  611   30  549 

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

[1] 15888

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

[1] 0.8902

INFO:numexpr.utils:Note: NumExpr detected 56 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

Check convergence of parameters

Past versions of unnamed-chunk-12-1.png

Version	Author	Date
2749be9	sq-96	2022-05-12

     gene       snp 
0.0079441 0.0003125 

 gene   snp 
13.20 10.19 

[1] 105318

[1]    6870 6309950

   gene     snp 
0.00684 0.19087 

[1] 0.01537 1.07050

Genes with highest PIPs

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

Version	Author	Date
2749be9	sq-96	2022-05-12

       genename region_tag susie_pip   mu2       PVE      z num_intron num_sqtl
3252       LRP8       1_33    1.1226 33.65 0.0003019  4.820          5        5
2151   FAM177A1       14_9    1.0331 24.42 0.0002142 -4.872         12       14
2429     GIGYF1       7_62    1.0221 34.53 0.0002916  5.266          3        3
3237     LPCAT4      15_10    0.9460 25.64 0.0002120  4.892          3        3
3166  LINC00320       21_6    0.9267 29.45 0.0002312  5.336          3        3
671        BDNF      11_19    0.9135 23.62 0.0001837  4.348          3        4
749  BUB1B-PAK6      15_14    0.9025 30.73 0.0002351  5.588          2        2
613      B3GAT1      11_84    0.8969 23.77 0.0001658 -4.448          8       12
1471      CRTAP       3_24    0.8847 20.12 0.0001488  3.929          2        2
3324     MAD1L1        7_3    0.8812 69.62 0.0003687  8.182          6        7
5965      THAP8      19_25    0.8507 19.76 0.0001358 -3.847          2        2
4171      PCBP2      12_33    0.8426 26.30 0.0001773 -4.953          2        2
1707       DGKZ      11_28    0.8422 48.30 0.0003253  7.216          2        2
5577     SNRPA1      15_50    0.8264 22.99 0.0001397 -3.934          5        7
6184      TPGS2      18_20    0.8198 28.26 0.0001709 -4.088          4        4
416      APOPT1      14_54    0.7858 46.02 0.0002582 -7.407          7       10
4000      NT5C2      10_66    0.7796 48.83 0.0002566 -8.541         11       13
141      ACTR1B       2_57    0.7780 20.17 0.0001136  3.978          5        5
325      ANAPC7      12_67    0.7579 38.23 0.0001921  6.385          4        4
5307      SF3B1      2_117    0.7509 46.51 0.0002443 -7.053          2        2

Genes with highest PVE

       genename region_tag susie_pip   mu2       PVE      z num_intron num_sqtl
3324     MAD1L1        7_3    0.8812 69.62 0.0003687  8.182          6        7
1707       DGKZ      11_28    0.8422 48.30 0.0003253  7.216          2        2
3252       LRP8       1_33    1.1226 33.65 0.0003019  4.820          5        5
2429     GIGYF1       7_62    1.0221 34.53 0.0002916  5.266          3        3
416      APOPT1      14_54    0.7858 46.02 0.0002582 -7.407          7       10
4000      NT5C2      10_66    0.7796 48.83 0.0002566 -8.541         11       13
5307      SF3B1      2_117    0.7509 46.51 0.0002443 -7.053          2        2
749  BUB1B-PAK6      15_14    0.9025 30.73 0.0002351  5.588          2        2
3166  LINC00320       21_6    0.9267 29.45 0.0002312  5.336          3        3
2151   FAM177A1       14_9    1.0331 24.42 0.0002142 -4.872         12       14
3237     LPCAT4      15_10    0.9460 25.64 0.0002120  4.892          3        3
325      ANAPC7      12_67    0.7579 38.23 0.0001921  6.385          4        4
671        BDNF      11_19    0.9135 23.62 0.0001837  4.348          3        4
4171      PCBP2      12_33    0.8426 26.30 0.0001773 -4.953          2        2
6184      TPGS2      18_20    0.8198 28.26 0.0001709 -4.088          4        4
613      B3GAT1      11_84    0.8969 23.77 0.0001658 -4.448          8       12
1471      CRTAP       3_24    0.8847 20.12 0.0001488  3.929          2        2
5577     SNRPA1      15_50    0.8264 22.99 0.0001397 -3.934          5        7
2348       FXR1      3_111    0.5794 44.40 0.0001380  6.837          4        4
5965      THAP8      19_25    0.8507 19.76 0.0001358 -3.847          2        2

Comparing z scores and PIPs

Past versions of unnamed-chunk-16-1.png

Version	Author	Date
2749be9	sq-96	2022-05-12

Past versions of unnamed-chunk-16-2.png

Version	Author	Date
2749be9	sq-96	2022-05-12

[1] 0.01805

         genename region_tag susie_pip    mu2       PVE       z num_intron
3284         LSM2       6_26 9.745e-05 222.29 2.004e-11 -11.599          1
626          BAG6       6_26 1.158e-04 221.94 2.757e-11 -11.590          5
1657         DDR1       6_25 1.826e-01 105.59 3.276e-05  11.175          2
879      C6orf136       6_24 1.015e-01  82.59 8.072e-06 -11.031          2
2295        FLOT1       6_24 2.106e-01  81.23 3.399e-05 -10.981          6
745        BTN3A2       6_20 1.394e-01  92.71 8.680e-06 -10.665          5
4528         PPT2       6_26 3.691e-05 152.97 1.889e-12 -10.061          5
1923        EGFL8       6_26 2.931e-05 142.24 1.098e-12  -9.625          4
1072       CCHCR1       6_25 3.239e-02  68.64 3.490e-07  -9.508          6
2535        GPSM3       6_26 2.168e-06 124.08 5.539e-15   9.377          1
6706      ZKSCAN3       6_22 9.297e-03  58.35 4.789e-08  -9.321          1
2692      HLA-DMA       6_27 1.319e-01  69.70 4.883e-06   8.727          6
4000        NT5C2      10_66 7.796e-01  48.83 2.566e-04  -8.541         11
3324       MAD1L1        7_3 8.812e-01  69.62 3.687e-04   8.182          6
6271      TSNARE1       8_93 3.299e-02  53.87 3.712e-07   7.961          4
4259        PGBD1       6_22 3.918e-02  40.35 3.080e-07  -7.746          2
743        BTN2A1       6_20 4.151e-02  51.43 3.563e-07  -7.727          3
5073 RP5-874C20.8       6_22 3.226e-02  38.78 2.883e-07   7.631          4
744        BTN3A1       6_20 5.359e-02  47.80 4.827e-07   7.490          4
720          BRD2       6_27 2.136e-01  46.77 1.498e-05   7.455          6
     num_sqtl
3284        1
626         6
1657        2
879         2
2295        6
745         5
4528        5
1923        5
1072        9
2535        1
6706        1
2692       10
4000       13
3324        7
6271        6
4259        2
743         3
5073        4
744         4
720         7

GO enrichment analysis for genes with PIP>0.5

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

[1] 51

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-19-1.png

Version	Author	Date
2749be9	sq-96	2022-05-12

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

Past versions of unnamed-chunk-19-2.png

Version	Author	Date
2749be9	sq-96	2022-05-12

                                              Term Overlap Adjusted.P.value
1 protein phosphatase type 2A complex (GO:0000159)    2/17          0.03387
2                            U2 snRNP (GO:0005686)    2/20          0.03387
3            microtubule cytoskeleton (GO:0015630)   5/331          0.03387
                                Genes
1                     PPP2R5B;PPP2R2A
2                        SNRPA1;SF3B1
3 DYNC1I2;ACTR1B;ANAPC7;KIF21B;MAD1L1
[1] "GO_Molecular_Function_2021"

Past versions of unnamed-chunk-19-3.png

Version	Author	Date
2749be9	sq-96	2022-05-12

[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 BgRatio
238                           Abnormality of head or neck 0.01257  2/22  5/9703
17                             Adenocarcinoma of prostate 0.02914  2/22 20/9703
54                                                Measles 0.02914  1/22  1/9703
93                          Electroencephalogram abnormal 0.02914  1/22  1/9703
199                             Sporadic Breast Carcinoma 0.02914  1/22  1/9703
205                          Primary peritoneal carcinoma 0.02914  1/22  1/9703
208                      Osteogenesis Imperfecta Type VII 0.02914  1/22  1/9703
211 BREAST-OVARIAN CANCER, FAMILIAL, SUSCEPTIBILITY TO, 1 0.02914  1/22  1/9703
212         BREAST CANCER, FAMILIAL, SUSCEPTIBILITY TO, 1 0.02914  1/22  1/9703
213        OVARIAN CANCER, FAMILIAL, SUSCEPTIBILITY TO, 1 0.02914  1/22  1/9703

WebGestalt enrichment analysis for genes with PIP>0.5

Warning: replacing previous import 'lifecycle::last_warnings' by
'rlang::last_warnings' when loading 'hms'

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: 1 unlabeled data points (too many overlaps). Consider
increasing max.overlaps

Past versions of unnamed-chunk-22-1.png

Version	Author	Date
7d08c9b	sq-96	2022-05-18
2749be9	sq-96	2022-05-12

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] 51

#significance threshold for TWAS
print(sig_thresh)

[1] 4.485

#number of ctwas genes
length(ctwas_genes)

[1] 15

#number of TWAS genes
length(twas_genes)

[1] 124

#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_intron num_sqtl
613    B3GAT1      11_84    0.8969 23.77 0.0001658 -4.448          8       12
671      BDNF      11_19    0.9135 23.62 0.0001837  4.348          3        4
1471    CRTAP       3_24    0.8847 20.12 0.0001488  3.929          2        2
5577   SNRPA1      15_50    0.8264 22.99 0.0001397 -3.934          5        7
5965    THAP8      19_25    0.8507 19.76 0.0001358 -3.847          2        2
6184    TPGS2      18_20    0.8198 28.26 0.0001709 -4.088          4        4

#sensitivity / recall
print(sensitivity)

  ctwas    TWAS 
0.02308 0.13077 

#specificity
print(specificity)

 ctwas   TWAS 
0.9982 0.9843 

#precision / PPV
print(precision)

 ctwas   TWAS 
0.2000 0.1371 

Session information

sessionInfo()

R version 4.1.0 (2021-05-18)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)

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_1.4.0      forcats_0.5.1     stringr_1.4.0     purrr_0.3.4      
 [5] readr_1.4.0       tidyr_1.1.3       tidyverse_1.3.1   tibble_3.1.7     
 [9] WebGestaltR_0.4.4 disgenet2r_0.99.2 enrichR_3.0       cowplot_1.1.1    
[13] ggplot2_3.3.5     dplyr_1.0.7       reticulate_1.25   workflowr_1.7.0  

loaded via a namespace (and not attached):
 [1] fs_1.5.0          lubridate_1.7.10  doParallel_1.0.16 httr_1.4.2       
 [5] rprojroot_2.0.2   tools_4.1.0       backports_1.2.1   doRNG_1.8.2      
 [9] bslib_0.2.5.1     utf8_1.2.1        R6_2.5.0          vipor_0.4.5      
[13] DBI_1.1.1         colorspace_2.0-2  withr_2.4.2       ggrastr_1.0.1    
[17] tidyselect_1.1.1  processx_3.5.2    curl_4.3.2        compiler_4.1.0   
[21] git2r_0.28.0      rvest_1.0.0       cli_3.0.0         Cairo_1.5-15     
[25] xml2_1.3.2        labeling_0.4.2    sass_0.4.0        scales_1.1.1     
[29] callr_3.7.0       systemfonts_1.0.4 apcluster_1.4.9   digest_0.6.27    
[33] rmarkdown_2.9     svglite_2.0.0     pkgconfig_2.0.3   htmltools_0.5.1.1
[37] dbplyr_2.1.1      highr_0.9         rlang_1.0.2       rstudioapi_0.13  
[41] jquerylib_0.1.4   farver_2.1.0      generics_0.1.0    jsonlite_1.7.2   
[45] magrittr_2.0.1    Matrix_1.3-3      ggbeeswarm_0.6.0  Rcpp_1.0.7       
[49] munsell_0.5.0     fansi_0.5.0       lifecycle_1.0.0   stringi_1.6.2    
[53] whisker_0.4       yaml_2.2.1        plyr_1.8.6        grid_4.1.0       
[57] ggrepel_0.9.1     parallel_4.1.0    promises_1.2.0.1  crayon_1.4.1     
[61] lattice_0.20-44   haven_2.4.1       hms_1.1.0         knitr_1.33       
[65] ps_1.6.0          pillar_1.7.0      igraph_1.2.6      rjson_0.2.20     
[69] rngtools_1.5      reshape2_1.4.4    codetools_0.2-18  reprex_2.0.0     
[73] glue_1.4.2        evaluate_0.14     getPass_0.2-2     modelr_0.1.8     
[77] data.table_1.14.0 png_0.1-7         vctrs_0.3.8       httpuv_1.6.1     
[81] foreach_1.5.1     cellranger_1.1.0  gtable_0.3.0      assertthat_0.2.1 
[85] xfun_0.24         broom_0.7.8       later_1.2.0       iterators_1.0.13 
[89] beeswarm_0.4.0    ellipsis_0.3.2    here_1.0.1