Last updated: 2022-05-19

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Knit directory: cTWAS_analysis/

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File Version Author Date Message
Rmd 7d08c9b sq-96 2022-05-18 update
html 7d08c9b sq-96 2022-05-18 update
Rmd 2749be9 sq-96 2022-05-12 update
html 2749be9 sq-96 2022-05-12 update
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Rmd 6c6abbd sq-96 2022-05-12 update 
library(reticulate)
use_python("/scratch/midway2/shengqian/miniconda3/envs/PythonForR/bin/python",required=T)

Weight QC

#number of imputed weights
nrow(qclist_all)
[1] 15774
#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 
1480 1078  891  631  654  819  931  556  642  735  948  858  322  583  532  618 
  17   18   19   20   21   22 
1087  198 1146  543   34  488 
#number of imputed weights without missing variants
sum(qclist_all$nmiss==0)
[1] 14087
#proportion of imputed weights without missing variants
mean(qclist_all$nmiss==0)
[1] 0.8931
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

Version Author Date
2749be9 sq-96 2022-05-12 
     gene       snp 
0.0048321 0.0003214 
 gene   snp 
 9.84 10.49 
[1] 105318
[1]    6393 6309950
    gene      snp 
0.002886 0.202078 
[1] 0.007093 1.090103

Genes with highest PIPs

Version Author Date
2749be9 sq-96 2022-05-12 
      genename region_tag susie_pip   mu2       PVE      z num_intron num_sqtl
2889 LINC00320       21_6    1.0610 28.32 2.926e-04  5.336          6        6
2984      LRP8       1_33    0.9257 24.92 1.962e-04 -4.820          3        3
371     APOPT1      14_54    0.8221 43.94 2.808e-04 -7.429          5        6
6193   ZDHHC20       13_2    0.7562 24.63 1.313e-04 -4.784          3        4
2836     LAMA5      20_37    0.7084 30.04 1.381e-04 -4.371         10       14
1662    DPYSL3       5_86    0.7025 25.41 1.190e-04 -4.157          1        1
611       BDNF      11_19    0.6948 23.25 1.066e-04 -4.348          1        1
4020     PLCB2      15_14    0.6903 25.17 9.585e-05 -4.470          5        5
1554      DGKZ      11_28    0.6889 46.65 2.102e-04  7.216          2        2
552     B3GAT1      11_84    0.6636 25.37 9.490e-05  4.345          7       11
4326   PYROXD2      10_62    0.6365 24.28 8.561e-05  3.755         10       10
122     ACTR1B       2_57    0.6179 21.59 7.826e-05  3.978          3        3
1482     DBF4B      17_26    0.5949 20.61 6.733e-05 -3.890          4        4
3695     NTRK3      15_41    0.5946 22.72 7.628e-05 -4.457          1        1
5579     TMED4       7_32    0.5724 22.25 6.781e-05 -4.862          3        3
781    C2orf80      2_123    0.5393 25.65 5.402e-05 -3.011         10       12
235       AKT3      1_128    0.5277 34.14 8.384e-05  6.266          5        5
6256    ZNF211      19_39    0.5206 22.95 5.737e-05 -3.624          4        5
510     ATP2B2        3_8    0.4886 31.83 6.736e-05  4.229          3        3
1213     CNIH3      1_114    0.4872 21.03 4.196e-05 -3.852          7        9

Genes with highest PVE

      genename region_tag susie_pip   mu2       PVE      z num_intron num_sqtl
2889 LINC00320       21_6    1.0610 28.32 2.926e-04  5.336          6        6
371     APOPT1      14_54    0.8221 43.94 2.808e-04 -7.429          5        6
1554      DGKZ      11_28    0.6889 46.65 2.102e-04  7.216          2        2
2984      LRP8       1_33    0.9257 24.92 1.962e-04 -4.820          3        3
2836     LAMA5      20_37    0.7084 30.04 1.381e-04 -4.371         10       14
6193   ZDHHC20       13_2    0.7562 24.63 1.313e-04 -4.784          3        4
1662    DPYSL3       5_86    0.7025 25.41 1.190e-04 -4.157          1        1
611       BDNF      11_19    0.6948 23.25 1.066e-04 -4.348          1        1
4020     PLCB2      15_14    0.6903 25.17 9.585e-05 -4.470          5        5
552     B3GAT1      11_84    0.6636 25.37 9.490e-05  4.345          7       11
4326   PYROXD2      10_62    0.6365 24.28 8.561e-05  3.755         10       10
3686     NT5C2      10_66    0.4472 46.77 8.490e-05 -8.511          7        9
235       AKT3      1_128    0.5277 34.14 8.384e-05  6.266          5        5
4906     SF3B1      2_117    0.4467 43.83 8.117e-05  7.002          2        2
122     ACTR1B       2_57    0.6179 21.59 7.826e-05  3.978          3        3
3695     NTRK3      15_41    0.5946 22.72 7.628e-05 -4.457          1        1
5579     TMED4       7_32    0.5724 22.25 6.781e-05 -4.862          3        3
510     ATP2B2        3_8    0.4886 31.83 6.736e-05  4.229          3        3
1482     DBF4B      17_26    0.5949 20.61 6.733e-05 -3.890          4        4
3636    NPEPL1      20_34    0.4865 34.73 6.584e-05  3.996         13       15

Comparing z scores and PIPs

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

Version Author Date
2749be9 sq-96 2022-05-12 
[1] 0.01611
         genename region_tag susie_pip    mu2       PVE       z num_intron
3933        PGBD1       6_22 1.867e-02 157.22 2.841e-07 -13.087          2
370          APOM       6_26 2.029e-01 123.81 4.840e-05  11.541          2
1506         DDR1       6_26 1.524e-02 119.73 2.641e-07 -11.175          2
480         ATAT1       6_24 2.265e-02  79.41 3.868e-07  11.039          1
795      C6orf136       6_24 4.367e-02  79.12 1.433e-06 -11.031          2
2082        FLOT1       6_24 1.053e-01  77.80 8.177e-06 -10.981          6
568          BAG6       6_26 5.880e-04 108.10 3.549e-10 -10.247          4
4565         RNF5       6_26 6.016e-05  96.37 3.312e-12  -9.714          1
968        CCHCR1       6_26 8.126e-10  89.72 5.578e-22  -9.376          8
3686        NT5C2      10_66 4.472e-01  46.77 8.490e-05  -8.511          7
3043       MAD1L1        7_3 2.348e-01  63.35 2.501e-05  -8.215          3
2468        HLA-F       6_23 3.791e-02  61.03 6.413e-07  -8.066          2
2209       GIGYF2      2_137 3.745e-01  50.80 5.226e-05  -7.841          4
4685 RP5-874C20.8       6_22 2.206e-02  37.39 1.296e-07   7.631          4
6384      ZSCAN16       6_22 1.933e-02  52.88 1.201e-07   7.468          3
371        APOPT1      14_54 8.221e-01  43.94 2.808e-04  -7.429          5
1554         DGKZ      11_28 6.889e-01  46.65 2.102e-04   7.216          2
4968       SKIV2L       6_26 2.813e-08  77.27 5.804e-19   7.101          4
4906        SF3B1      2_117 4.467e-01  43.83 8.117e-05   7.002          2
485         ATG13      11_28 1.646e-01  43.02 1.107e-05   6.977          2
     num_sqtl
3933        3
370         2
1506        2
480         1
795         2
2082        6
568         6
4565        1
968        12
3686        9
3043        3
2468        3
2209        4
4685        4
6384        3
371         6
1554        2
4968        5
4906        2
485         2

GO enrichment analysis for genes with PIP>0.5

#number of genes for gene set enrichment
length(genes)
[1] 18
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"

Version Author Date
2749be9 sq-96 2022-05-12 
                                                                  Term Overlap
1    positive regulation of neuron projection development (GO:0010976)    4/88
2         positive regulation of phospholipase C activity (GO:0010863)    3/43
3            modulation of chemical synaptic transmission (GO:0050804)   3/109
4     positive regulation of cell projection organization (GO:0031346)   3/117
5       cellular response to nerve growth factor stimulus (GO:1990090)    2/22
6                  activation of phospholipase C activity (GO:0007202)    2/32
7             regulation of neuron projection development (GO:0010975)   3/165
8                  regulation of trans-synaptic signaling (GO:0099177)    2/35
9 positive regulation of protein tyrosine kinase activity (GO:0061098)    2/42
  Adjusted.P.value                  Genes
1        0.0002400 BDNF;NTRK3;DPYSL3;LRP8
2        0.0008678       BDNF;NTRK3;PLCB2
3        0.0082176         BDNF;DGKZ;LRP8
4        0.0082176      BDNF;NTRK3;DPYSL3
5        0.0082176             BDNF;NTRK3
6        0.0131378             BDNF;PLCB2
7        0.0131378      BDNF;NTRK3;DPYSL3
8        0.0131378              BDNF;LRP8
9        0.0168359              BDNF;LRP8
[1] "GO_Cellular_Component_2021"

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_Molecular_Function_2021"

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
49                                                  Status Epilepticus 0.01491
53                                                 Unipolar Depression 0.01491
75                                                    Petit mal status 0.01491
82                                        Grand Mal Status Epilepticus 0.01491
87                                  Complex Partial Status Epilepticus 0.01491
119                                    Status Epilepticus, Subclinical 0.01491
120                                  Non-Convulsive Status Epilepticus 0.01491
121                                  Simple Partial Status Epilepticus 0.01491
124                                          Major Depressive Disorder 0.01491
142 MEGALENCEPHALY-POLYMICROGYRIA-POLYDACTYLY-HYDROCEPHALUS SYNDROME 2 0.01491
    Ratio  BgRatio
49    2/7  68/9703
53    3/7 259/9703
75    2/7  67/9703
82    2/7  67/9703
87    2/7  67/9703
119   2/7  67/9703
120   2/7  67/9703
121   2/7  67/9703
124   3/7 243/9703
142   1/7   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

Version Author Date
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$genename))
[1] 49
#significance threshold for TWAS
print(sig_thresh)
[1] 4.47
#number of ctwas genes
length(ctwas_genes)
[1] 3
#number of TWAS genes
length(twas_genes)
[1] 103
#show novel genes (ctwas genes with not in TWAS genes)
ctwas_gene_res[ctwas_gene_res$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 
0.007692 0.100000 
#specificity
print(specificity)
 ctwas   TWAS 
0.9997 0.9858 
#precision / PPV
print(precision)
 ctwas   TWAS 
0.3333 0.1262 

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