Last updated: 2022-05-19

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Knit directory: cTWAS_analysis/

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Rmd be614ed sq-96 2022-05-19 update
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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

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] 0.009055 1.070497

Genes with highest PIPs

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
3237     LPCAT4      15_10    0.9052 25.64 2.029e-04  4.892          3        3
749  BUB1B-PAK6      15_14    0.8895 30.73 2.317e-04  5.588          2        2
3166  LINC00320       21_6    0.8675 29.45 2.164e-04  5.336          3        3
6184      TPGS2      18_20    0.7685 28.26 1.602e-04 -4.088          4        4
1835     DPYSL3       5_86    0.7392 22.59 1.172e-04 -4.157          1        1
5307      SF3B1      2_117    0.7296 46.51 2.374e-04 -7.053          2        2
6674    ZDHHC20       13_2    0.7181 23.83 1.177e-04 -4.615          2        2
1714       DHPS      19_10    0.7106 24.82 1.190e-04 -4.396          1        1
2151   FAM177A1       14_9    0.7085 24.42 1.469e-04 -4.872         12       14
2429     GIGYF1       7_62    0.7004 34.53 1.998e-04  5.266          3        3
325      ANAPC7      12_67    0.6295 38.23 1.595e-04  6.385          4        4
621        B9D1      17_16    0.5939 28.83 1.024e-04  5.282          2        2
3324     MAD1L1        7_3    0.5904 69.62 2.470e-04  8.182          6        7
992       CASP2       7_89    0.5743 21.16 6.628e-05 -3.889          1        1
565      ATP2B2        3_8    0.5679 26.51 8.118e-05  4.229          1        1
613      B3GAT1      11_84    0.5295 23.77 9.786e-05 -4.448          8       12
1620      DBF4B      17_26    0.5257 21.62 5.710e-05 -3.890          2        2
2772       ICE1        5_5    0.5167 26.91 6.996e-05 -3.766          2        2
5577     SNRPA1      15_50    0.5078 22.99 8.584e-05 -3.934          5        7
3252       LRP8       1_33    0.5022 33.65 1.350e-04  4.820          5        5

Genes with highest PVE

       genename region_tag susie_pip   mu2       PVE      z num_intron num_sqtl
3324     MAD1L1        7_3    0.5904 69.62 2.470e-04  8.182          6        7
5307      SF3B1      2_117    0.7296 46.51 2.374e-04 -7.053          2        2
749  BUB1B-PAK6      15_14    0.8895 30.73 2.317e-04  5.588          2        2
3166  LINC00320       21_6    0.8675 29.45 2.164e-04  5.336          3        3
3237     LPCAT4      15_10    0.9052 25.64 2.029e-04  4.892          3        3
2429     GIGYF1       7_62    0.7004 34.53 1.998e-04  5.266          3        3
416      APOPT1      14_54    0.5005 46.02 1.645e-04 -7.407          7       10
1707       DGKZ      11_28    0.4211 48.30 1.626e-04  7.216          2        2
6184      TPGS2      18_20    0.7685 28.26 1.602e-04 -4.088          4        4
325      ANAPC7      12_67    0.6295 38.23 1.595e-04  6.385          4        4
2151   FAM177A1       14_9    0.7085 24.42 1.469e-04 -4.872         12       14
4000      NT5C2      10_66    0.4284 48.83 1.410e-04 -8.541         11       13
3252       LRP8       1_33    0.5022 33.65 1.350e-04  4.820          5        5
1714       DHPS      19_10    0.7106 24.82 1.190e-04 -4.396          1        1
6674    ZDHHC20       13_2    0.7181 23.83 1.177e-04 -4.615          2        2
1835     DPYSL3       5_86    0.7392 22.59 1.172e-04 -4.157          1        1
621        B9D1      17_16    0.5939 28.83 1.024e-04  5.282          2        2
671        BDNF      11_19    0.4914 23.62 9.879e-05  4.348          3        4
613      B3GAT1      11_84    0.5295 23.77 9.786e-05 -4.448          8       12
4171      PCBP2      12_33    0.4213 26.30 8.863e-05 -4.953          2        2

Comparing z scores and PIPs

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

Version Author Date
be614ed sq-96 2022-05-19
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 1.124e-04 221.94 2.676e-11 -11.590          5
1657         DDR1       6_25 1.717e-01 105.59 3.080e-05  11.175          2
879      C6orf136       6_24 5.073e-02  82.59 4.036e-06 -11.031          2
2295        FLOT1       6_24 4.039e-02  81.23 6.519e-06 -10.981          6
745        BTN3A2       6_20 7.395e-02  92.71 4.606e-06 -10.665          5
4528         PPT2       6_26 3.481e-05 152.97 1.782e-12 -10.061          5
1923        EGFL8       6_26 2.741e-05 142.24 1.027e-12  -9.625          4
1072       CCHCR1       6_25 1.143e-02  68.64 1.231e-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 3.701e-02  69.70 1.370e-06   8.727          6
4000        NT5C2      10_66 4.284e-01  48.83 1.410e-04  -8.541         11
3324       MAD1L1        7_3 5.904e-01  69.62 2.470e-04   8.182          6
6271      TSNARE1       8_93 1.806e-02  53.87 2.032e-07   7.961          4
4259        PGBD1       6_22 2.892e-02  40.35 2.273e-07  -7.746          2
743        BTN2A1       6_20 1.458e-02  51.43 1.251e-07  -7.727          3
5073 RP5-874C20.8       6_22 8.659e-03  38.78 7.738e-08   7.631          4
744        BTN3A1       6_20 1.358e-02  47.80 1.223e-07   7.490          4
720          BRD2       6_27 1.523e-01  46.77 1.067e-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] 21
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
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"

Version Author Date
be614ed sq-96 2022-05-19
2749be9 sq-96 2022-05-12
                                           Term Overlap Adjusted.P.value
1                         U2 snRNP (GO:0005686)    2/20         0.007298
2 U2-type precatalytic spliceosome (GO:0071005)    2/50         0.012478
3       spliceosomal snRNP complex (GO:0097525)    2/51         0.012478
4         precatalytic spliceosome (GO:0071011)    2/52         0.012478
5     U2-type spliceosomal complex (GO:0005684)    2/89         0.028799
         Genes
1 SNRPA1;SF3B1
2 SNRPA1;SF3B1
3 SNRPA1;SF3B1
4 SNRPA1;SF3B1
5 SNRPA1;SF3B1
[1] "GO_Molecular_Function_2021"

Version Author Date
be614ed sq-96 2022-05-19
2749be9 sq-96 2022-05-12
                                                                                                   Term
1               acyltransferase activity, transferring groups other than amino-acyl groups (GO:0016747)
2                                                                         U2 snRNA binding (GO:0030620)
3                                   1-acylglycerophosphocholine O-acyltransferase activity (GO:0047184)
4                                                             dihydropyrimidinase activity (GO:0004157)
5                                                lysophospholipid acyltransferase activity (GO:0071617)
6                                                             O-acetyltransferase activity (GO:0016413)
7                                                      P-type calcium transporter activity (GO:0005388)
8  hydrolase activity, acting on carbon-nitrogen (but not peptide) bonds, in cyclic amides (GO:0016812)
9             cysteine-type endopeptidase activity involved in apoptotic signaling pathway (GO:0097199)
10                                                                         filamin binding (GO:0031005)
11           cysteine-type endopeptidase activity involved in execution phase of apoptosis (GO:0097200)
12                                                         P-type ion transporter activity (GO:0015662)
13                      cysteine-type endopeptidase activity involved in apoptotic process (GO:0097153)
   Overlap Adjusted.P.value          Genes
1     2/76          0.04070 ZDHHC20;LPCAT4
2      1/5          0.04070         SNRPA1
3      1/6          0.04070         LPCAT4
4      1/6          0.04070         DPYSL3
5      1/8          0.04070         LPCAT4
6      1/8          0.04070         LPCAT4
7      1/9          0.04070         ATP2B2
8     1/10          0.04070         DPYSL3
9     1/10          0.04070          CASP2
10    1/11          0.04070         DPYSL3
11    1/13          0.04070          CASP2
12    1/13          0.04070         ATP2B2
13    1/15          0.04331          CASP2

DisGeNET enrichment analysis for genes with PIP>0.5

                                  Description     FDR Ratio BgRatio
18              Electroencephalogram abnormal 0.01366   1/8  1/9703
34 Refractory anemia with ringed sideroblasts 0.01366   1/8  2/9703
41           Deafness, Autosomal Recessive 12 0.01366   1/8  2/9703
43                  Prostate cancer, familial 0.01366   2/8 69/9703
46                    MECKEL SYNDROME, TYPE 9 0.01366   1/8  1/9703
54                        JOUBERT SYNDROME 27 0.01366   1/8  1/9703
58             PROSTATE CANCER, HEREDITARY, 1 0.01366   2/8 60/9703
26                 Malignant melanoma of iris 0.02388   1/8  5/9703
27              Malignant melanoma of choroid 0.02388   1/8  5/9703
52                Abnormality of head or neck 0.02388   1/8  5/9703

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
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$genename))
[1] 51
#significance threshold for TWAS
print(sig_thresh)
[1] 4.485
#number of ctwas genes
length(ctwas_genes)
[1] 3
#number of TWAS genes
length(twas_genes)
[1] 124
#show novel genes (ctwas genes with not in TWAS genes)
ctwas_gene_res[ctwas_gene_res$genename %in% novel_genes,report_cols]
[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 0.130769 
#specificity
print(specificity)
 ctwas   TWAS 
0.9997 0.9843 
#precision / PPV
print(precision)
 ctwas   TWAS 
0.3333 0.1371 

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