SCZ 2018 - Brain_Spinal_cord_cervical_c-1
sheng Qian
2021-2-6
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] 18945#number of imputed weights by chromosome
table(qclist_all$chr)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1715 1338 1100 796 767 1008 1092 641 786 887 1173 1022 398 671 695 738
17 18 19 20 21 22
1343 294 1317 607 40 517 #number of imputed weights without missing variants
sum(qclist_all$nmiss==0)[1] 16803#proportion of imputed weights without missing variants
mean(qclist_all$nmiss==0)[1] 0.8869INFO: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, lagThe following objects are masked from 'package:base':
intersect, setdiff, setequal, unionCheck convergence of parameters
| Version | Author | Date |
|---|---|---|
| 2749be9 | sq-96 | 2022-05-12 |
gene snp
0.0076295 0.0003131 gene snp
11.87 10.31 [1] 105318[1] 7065 6309950 gene snp
0.006076 0.193399 [1] 0.01706 1.11082Genes with highest PIPs
genename region_tag susie_pip mu2 PVE z num_intron
2184 FAM177A1 14_9 1.0733 23.92 0.0002148 4.849 15
4793 R3HDM2 12_36 1.0282 43.35 0.0004166 -6.634 4
684 BDNF 11_19 0.9214 22.76 0.0001801 4.348 4
3152 LAMA5 20_36 0.9075 24.09 0.0001723 -4.329 11
6106 THAP8 19_25 0.8578 19.74 0.0001376 3.847 2
630 B3GAT1 11_84 0.8550 21.97 0.0001383 4.272 7
5428 SF3B1 2_117 0.8501 45.64 0.0003002 7.053 4
434 APOPT1 14_54 0.8410 45.01 0.0002955 7.429 6
4751 PTPRF 1_27 0.8342 37.73 0.0002420 6.680 4
4439 PLCB2 15_14 0.8314 24.84 0.0001344 -4.470 6
4737 PTPA 9_66 0.8179 23.79 0.0001480 -4.650 5
1532 CTC-487M23.8 5_67 0.8126 21.51 0.0001335 -4.125 2
274 AKT3 1_128 0.7738 35.42 0.0001884 -6.291 6
144 ACTR1B 2_57 0.7606 20.11 0.0001094 -3.978 4
3701 MRPS33 7_87 0.7403 24.49 0.0001196 4.304 5
2129 EXTL2 1_62 0.7386 22.86 0.0001145 -3.966 3
1859 DST 6_42 0.7365 29.73 0.0001294 4.205 8
5349 SDCCAG8 1_128 0.7307 26.43 0.0001288 5.301 8
1849 DPYSL3 5_86 0.7277 22.63 0.0001138 -4.157 1
1486 CRTAP 3_24 0.7270 22.03 0.0001106 3.929 1
num_sqtl
2184 16
4793 4
684 4
3152 14
6106 2
630 10
5428 4
434 9
4751 4
4439 7
4737 5
1532 2
274 6
144 4
3701 7
2129 5
1859 9
5349 11
1849 1
1486 1Genes with highest PVE
genename region_tag susie_pip mu2 PVE z num_intron
433 APOM 6_26 0.4991 639.82 0.0015126 -11.590 3
4793 R3HDM2 12_36 1.0282 43.35 0.0004166 -6.634 4
5428 SF3B1 2_117 0.8501 45.64 0.0003002 7.053 4
434 APOPT1 14_54 0.8410 45.01 0.0002955 7.429 6
4751 PTPRF 1_27 0.8342 37.73 0.0002420 6.680 4
2184 FAM177A1 14_9 1.0733 23.92 0.0002148 4.849 15
1729 DGKZ 11_28 0.6904 47.56 0.0002134 -7.216 3
4070 NT5C2 10_66 0.6840 47.62 0.0001954 -8.511 10
274 AKT3 1_128 0.7738 35.42 0.0001884 -6.291 6
6634 VARS 6_26 0.1755 640.87 0.0001874 -11.548 1
684 BDNF 11_19 0.9214 22.76 0.0001801 4.348 4
5988 TAOK2 16_24 0.6314 47.43 0.0001738 7.024 3
3152 LAMA5 20_36 0.9075 24.09 0.0001723 -4.329 11
4737 PTPA 9_66 0.8179 23.79 0.0001480 -4.650 5
630 B3GAT1 11_84 0.8550 21.97 0.0001383 4.272 7
6106 THAP8 19_25 0.8578 19.74 0.0001376 3.847 2
4439 PLCB2 15_14 0.8314 24.84 0.0001344 -4.470 6
1532 CTC-487M23.8 5_67 0.8126 21.51 0.0001335 -4.125 2
1859 DST 6_42 0.7365 29.73 0.0001294 4.205 8
5349 SDCCAG8 1_128 0.7307 26.43 0.0001288 5.301 8
num_sqtl
433 3
4793 4
5428 4
434 9
4751 4
2184 16
1729 3
4070 14
274 6
6634 1
684 4
5988 3
3152 14
4737 5
630 10
6106 2
4439 7
1532 2
1859 9
5349 11Comparing z scores and PIPs
[1] 0.01699 genename region_tag susie_pip mu2 PVE z num_intron
4339 PGBD1 6_22 6.031e-02 161.09 3.090e-06 13.087 3
433 APOM 6_26 4.991e-01 639.82 1.513e-03 -11.590 3
6634 VARS 6_26 1.755e-01 640.87 1.874e-04 -11.548 1
883 C6orf136 6_24 8.488e-02 80.36 5.498e-06 11.031 2
2329 FLOT1 6_24 2.639e-01 80.69 5.241e-05 -10.981 8
3350 LST1 6_25 2.759e-02 94.96 5.477e-07 -10.892 3
763 BTN3A2 6_20 1.055e-01 92.12 4.453e-06 -10.665 5
641 BAG6 6_26 1.878e-09 511.85 1.714e-20 -10.247 6
4613 PPT2 6_26 4.883e-12 476.52 1.079e-25 -10.061 4
2575 GPSM3 6_26 1.208e-12 426.07 5.903e-27 9.608 1
6361 TRIM38 6_20 2.769e-02 74.35 3.015e-07 9.596 2
1069 CCHCR1 6_25 4.787e-02 67.97 6.243e-07 -9.508 8
1944 EGFL8 6_26 1.443e-15 362.39 7.168e-33 -9.298 4
1675 DDR1 6_25 1.294e-02 70.64 1.123e-07 9.016 1
2736 HLA-DMA 6_27 3.059e-01 76.01 3.919e-05 8.588 7
7059 ZSCAN23 6_22 9.038e-03 46.89 3.637e-08 8.541 1
4070 NT5C2 10_66 6.840e-01 47.62 1.954e-04 -8.511 10
3393 MAIP1 2_118 2.868e-01 45.08 3.521e-05 7.980 1
529 AS3MT 10_66 2.050e-01 42.75 1.691e-05 -7.907 2
5184 RP5-874C20.8 6_22 3.448e-02 38.07 3.077e-07 7.631 4
num_sqtl
4339 3
433 3
6634 1
883 2
2329 8
3350 3
763 5
641 6
4613 4
2575 2
6361 2
1069 12
1944 5
1675 1
2736 8
7059 1
4070 14
3393 1
529 2
5184 4GO enrichment analysis for genes with PIP>0.5
#number of genes for gene set enrichment
length(genes)[1] 53Uploading 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"
Term Overlap
1 positive regulation of neuron projection development (GO:0010976) 5/88
2 positive regulation of phospholipase C activity (GO:0010863) 3/43
3 positive regulation of cell projection organization (GO:0031346) 4/117
4 regulation of receptor binding (GO:1900120) 2/10
Adjusted.P.value Genes
1 0.001904 BDNF;NTRK3;DPYSL3;SERPINI1;LRP8
2 0.040757 BDNF;NTRK3;PLCB2
3 0.040757 BDNF;NTRK3;DPYSL3;SERPINI1
4 0.040757 BDNF;PTPRF
[1] "GO_Cellular_Component_2021"
Term Overlap Adjusted.P.value
1 protein phosphatase type 2A complex (GO:0000159) 2/17 0.04952
2 U2 snRNP (GO:0005686) 2/20 0.04952
Genes
1 PTPA;PPP2R2A
2 SNRPA1;SF3B1
[1] "GO_Molecular_Function_2021"
[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
55 Measles 0.03696 1/29
94 Electroencephalogram abnormal 0.03696 1/29
100 Congenital absent nipple 0.03696 1/29
156 Congenital absence of breast with absent nipple 0.03696 1/29
216 Atrial Fibrillation, Familial, 3 0.03696 1/29
220 Osteogenesis Imperfecta Type VII 0.03696 1/29
221 Familial encephalopathy with neuroserpin inclusion bodies 0.03696 1/29
224 SHORT QT SYNDROME 2 (disorder) 0.03696 1/29
229 Short Qt Syndrome 0.03696 1/29
231 HEMOLYTIC UREMIC SYNDROME, ATYPICAL, SUSCEPTIBILITY TO, 2 0.03696 1/29
BgRatio
55 1/9703
94 1/9703
100 1/9703
156 1/9703
216 1/9703
220 1/9703
221 1/9703
224 1/9703
229 1/9703
231 1/9703WebGestalt 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!NULLPIP Manhattan Plot
Warning: ggrepel: 8 unlabeled data points (too many overlaps). Consider
increasing max.overlaps
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] 46#significance threshold for TWAS
print(sig_thresh)[1] 4.491#number of ctwas genes
length(ctwas_genes)[1] 12#number of TWAS genes
length(twas_genes)[1] 120#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
630 B3GAT1 11_84 0.8550 21.97 0.0001383 4.272 7
684 BDNF 11_19 0.9214 22.76 0.0001801 4.348 4
1532 CTC-487M23.8 5_67 0.8126 21.51 0.0001335 -4.125 2
3152 LAMA5 20_36 0.9075 24.09 0.0001723 -4.329 11
4439 PLCB2 15_14 0.8314 24.84 0.0001344 -4.470 6
6106 THAP8 19_25 0.8578 19.74 0.0001376 3.847 2
num_sqtl
630 10
684 4
1532 2
3152 14
4439 7
6106 2#sensitivity / recall
print(sensitivity) ctwas TWAS
0.02308 0.12308 #specificity
print(specificity) ctwas TWAS
0.9987 0.9852 #precision / PPV
print(precision) ctwas TWAS
0.2500 0.1333
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