SCZ 2018 - Brain_Hypothalamus

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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] 19902

#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 
1843 1406 1208  781  846 1042 1147  677  814  921 1170 1073  396  705  657  781 
  17   18   19   20   21   22 
1382  282 1439  658   36  638 

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

[1] 17601

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

[1] 0.8844

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 
0.0083920 0.0003085 

 gene   snp 
11.94 10.24 

[1] 105318

[1]    7334 6309950

    gene      snp 
0.006979 0.189243 

[1] 0.01088 1.05816

Genes with highest PIPs

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

Version	Author	Date
be614ed	sq-96	2022-05-19
2749be9	sq-96	2022-05-12

      genename region_tag susie_pip   mu2       PVE      z num_intron num_sqtl
4991    R3HDM2      12_36    0.9690 43.52 4.166e-04 -6.634          4        4
4239     NRXN2      11_36    0.8816 24.81 1.863e-04  4.723          3        3
2566    GIGYF2      2_137    0.8442 56.62 3.961e-04  8.128          3        3
3351 LINC00320       21_6    0.8217 29.24 2.068e-04 -5.336          5        5
4951     PTPRF       1_27    0.8167 37.18 2.456e-04  6.680          4        4
1922    DPYSL3       5_86    0.7459 22.30 1.178e-04  4.157          1        1
2181      ETF1       5_82    0.7438 33.82 1.776e-04  6.112          1        1
6663   TSNARE1       8_93    0.7332 28.75 1.502e-04  5.782          7       10
1801      DHPS      19_10    0.7270 24.40 1.225e-04 -4.396          1        1
5639     SF3B1      2_117    0.7159 45.62 2.245e-04  7.053          2        2
3873    MRPS33       7_87    0.7137 23.44 1.175e-04 -4.304          4        5
7105   ZDHHC20       13_2    0.6964 24.67 1.144e-04 -4.784          2        3
3114     JSRP1       19_3    0.6911 24.40 1.114e-04 -4.350          2        2
7140      ZIC4       3_91    0.6794 23.46 1.320e-04 -4.221          3        4
4743     PP2D1       3_14    0.6713 23.37 1.004e-04  4.056          2        2
4953     PTPRK       6_85    0.6701 28.67 1.227e-04  5.059          2        2
1030     CASP2       7_89    0.5881 20.87 6.854e-05 -3.889          1        1
661       B9D1      17_16    0.5568 28.33 8.906e-05  5.282          2        2
442     APOPT1      14_54    0.5547 46.11 1.651e-04  7.429          4        7
4638     PLCB2      15_14    0.5423 21.99 6.628e-05 -4.470          5        5

Genes with highest PVE

      genename region_tag susie_pip   mu2       PVE      z num_intron num_sqtl
4991    R3HDM2      12_36    0.9690 43.52 0.0004166 -6.634          4        4
2566    GIGYF2      2_137    0.8442 56.62 0.0003961  8.128          3        3
4951     PTPRF       1_27    0.8167 37.18 0.0002456  6.680          4        4
5639     SF3B1      2_117    0.7159 45.62 0.0002245  7.053          2        2
3351 LINC00320       21_6    0.8217 29.24 0.0002068 -5.336          5        5
4239     NRXN2      11_36    0.8816 24.81 0.0001863  4.723          3        3
2181      ETF1       5_82    0.7438 33.82 0.0001776  6.112          1        1
442     APOPT1      14_54    0.5547 46.11 0.0001651  7.429          4        7
6663   TSNARE1       8_93    0.7332 28.75 0.0001502  5.782          7       10
7140      ZIC4       3_91    0.6794 23.46 0.0001320 -4.221          3        4
286       AKT3      1_128    0.4212 34.79 0.0001232 -6.291          8        8
4953     PTPRK       6_85    0.6701 28.67 0.0001227  5.059          2        2
1801      DHPS      19_10    0.7270 24.40 0.0001225 -4.396          1        1
2390     FEZF1       7_74    0.5016 24.62 0.0001195 -4.812          3        3
1922    DPYSL3       5_86    0.7459 22.30 0.0001178  4.157          1        1
3873    MRPS33       7_87    0.7137 23.44 0.0001175 -4.304          4        5
7105   ZDHHC20       13_2    0.6964 24.67 0.0001144 -4.784          2        3
3114     JSRP1       19_3    0.6911 24.40 0.0001114 -4.350          2        2
3449      LRP8       1_33    0.4998 23.82 0.0001068  4.654          3        4
4743     PP2D1       3_14    0.6713 23.37 0.0001004  4.056          2        2

Comparing z scores and PIPs

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

Version	Author	Date
be614ed	sq-96	2022-05-19
2749be9	sq-96	2022-05-12

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

Version	Author	Date
be614ed	sq-96	2022-05-19
2749be9	sq-96	2022-05-12

[1] 0.01773

         genename region_tag susie_pip    mu2       PVE       z num_intron
4531        PGBD1       6_22 3.311e-02 161.09 9.695e-07 -13.087          2
6901         VARS       6_26 8.163e-05 217.29 1.375e-11 -11.548          1
441          APOM       6_26 8.321e-05 217.08 1.428e-11 -11.541          2
1747         DDR1       6_25 1.384e-01 101.78 1.949e-05  11.175          2
6902        VARS2       6_25 1.018e-01 100.66 9.907e-06 -11.137          1
914      C6orf136       6_24 4.736e-02  80.92 3.447e-06 -11.031          2
2421        FLOT1       6_24 3.830e-02  79.57 7.323e-06  10.981          7
781        BTN3A2       6_20 2.473e-02  91.37 9.309e-07 -10.659          6
668          BAG6       6_26 2.608e-05 166.08 1.117e-12  10.247          7
2849        HLA-B       6_25 1.136e-02  79.14 2.188e-07  10.150         10
5245         RNF5       6_26 2.893e-05 150.34 1.195e-12 -10.045          1
1123       CCHCR1       6_25 1.249e-02  66.51 2.634e-07   9.508          9
2682        GPSM3       6_26 1.971e-06 122.29 4.509e-15  -9.377          1
4257        NT5C2      10_66 3.646e-01  48.79 7.262e-05  -8.511          8
5383 RP5-874C20.8       6_22 1.086e-02  46.81 1.237e-07   8.304          4
2566       GIGYF2      2_137 8.442e-01  56.62 3.961e-04   8.128          3
3887         MSH5       6_26 1.115e-05  72.41 1.089e-13   7.892          3
814      C12orf65      12_75 2.009e-01  55.60 2.131e-05  -7.754          1
7141      ZKSCAN3       6_22 1.184e-02  36.54 5.053e-08  -7.740          2
780        BTN3A1       6_20 1.476e-02  47.48 1.599e-07   7.490          5
     num_sqtl
4531        3
6901        1
441         2
1747        2
6902        1
914         2
2421        8
781         7
668        10
2849       19
5245        1
1123       13
2682        1
4257       12
5383        5
2566        3
3887        3
814         1
7141        2
780         5

GO enrichment analysis for genes with PIP>0.5

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

[1] 24

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
be614ed	sq-96	2022-05-19
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
be614ed	sq-96	2022-05-19
2749be9	sq-96	2022-05-12

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

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

Version	Author	Date
be614ed	sq-96	2022-05-19
2749be9	sq-96	2022-05-12

                                                                       Term
1          transmembrane receptor protein phosphatase activity (GO:0019198)
2 transmembrane receptor protein tyrosine phosphatase activity (GO:0005001)
  Overlap Adjusted.P.value       Genes
1    2/16         0.004016 PTPRK;PTPRF
2    2/16         0.004016 PTPRK;PTPRF

DisGeNET enrichment analysis for genes with PIP>0.5

                                                   Description     FDR Ratio
20                               Electroencephalogram abnormal 0.01393  1/16
23                                    Congenital absent nipple 0.01393  1/16
37             Congenital absence of breast with absent nipple 0.01393  1/16
58   Familial encephalopathy with neuroserpin inclusion bodies 0.01393  1/16
62                                     MECKEL SYNDROME, TYPE 9 0.01393  1/16
68         BREASTS AND/OR NIPPLES, APLASIA OR HYPOPLASIA OF, 2 0.01393  1/16
69    HYPOGONADOTROPIC HYPOGONADISM 22 WITH OR WITHOUT ANOSMIA 0.01393  1/16
71 PARKINSON DISEASE 11, AUTOSOMAL DOMINANT, SUSCEPTIBILITY TO 0.01393  1/16
73                                         JOUBERT SYNDROME 27 0.01393  1/16
49                  Refractory anemia with ringed sideroblasts 0.02277  1/16
   BgRatio
20  1/9703
23  1/9703
37  1/9703
58  1/9703
62  1/9703
68  1/9703
69  1/9703
71  1/9703
73  1/9703
49  2/9703

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

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

Version	Author	Date
be614ed	sq-96	2022-05-19
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] 50

#significance threshold for TWAS
print(sig_thresh)

[1] 4.499

#number of ctwas genes
length(ctwas_genes)

[1] 5

#number of TWAS genes
length(twas_genes)

[1] 130

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

[1] genename   region_tag susie_pip  mu2        PVE        z          num_intron
[8] num_sqtl  
<0 rows> (or 0-length row.names)

#sensitivity / recall
print(sensitivity)

  ctwas    TWAS 
0.01538 0.13077 

#specificity
print(specificity)

 ctwas   TWAS 
0.9996 0.9845 

#precision / PPV
print(precision)

 ctwas   TWAS 
0.4000 0.1308 

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