SCZ 2018 - Brain_Substantia_nigra
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] 15170#number of imputed weights by chromosome
table(qclist_all$chr)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1400 1082 880 623 588 770 877 489 649 714 913 791 301 549 531 626
17 18 19 20 21 22
1040 214 1116 542 34 441 #number of imputed weights without missing variants
sum(qclist_all$nmiss==0)[1] 13605#proportion of imputed weights without missing variants
mean(qclist_all$nmiss==0)[1] 0.8968INFO: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
0.0065597 0.0003205 gene snp
9.522 10.339 [1] 105318[1] 6278 6309950 gene snp
0.003723 0.198505 [1] 0.008784 1.088938Genes with highest PIPs
genename region_tag susie_pip mu2 PVE z num_intron num_sqtl
3022 LRP8 1_33 1.0645 32.61 2.549e-04 -4.624 6 6
1361 CRTAP 3_24 0.8430 20.01 1.343e-04 3.929 2 2
5465 THAP8 19_25 0.8114 20.21 1.261e-04 3.847 2 2
380 APOPT1 14_54 0.8024 44.24 2.642e-04 7.429 6 9
1685 DPYSL3 5_86 0.7628 23.36 1.291e-04 4.157 1 1
619 BDNF 11_19 0.7481 22.63 1.203e-04 4.348 1 1
564 B3GAT1 11_84 0.6722 31.39 1.272e-04 -4.516 6 10
241 AKT3 1_128 0.6713 34.01 1.356e-04 -6.291 6 6
4024 PLCB2 15_14 0.6378 24.42 8.300e-05 4.470 3 4
5949 VPS41 7_28 0.6151 25.12 8.874e-05 -4.509 2 2
129 ACTR1B 2_57 0.5934 22.34 7.367e-05 3.978 3 3
2308 GON4L 1_76 0.5783 27.63 8.773e-05 4.084 1 1
3192 MDK 11_28 0.5743 45.88 1.437e-04 7.159 1 1
2881 LAMA5 20_36 0.5692 32.47 8.011e-05 3.967 10 15
4326 PYROXD2 10_62 0.5608 33.32 7.427e-05 -3.718 10 11
2166 FXR1 3_111 0.5532 42.91 1.221e-04 -6.873 4 4
1022 CD46 1_105 0.5515 18.45 5.268e-05 -3.654 6 6
4280 PTK2B 8_27 0.5318 26.09 6.953e-05 4.730 2 3
2446 HDDC2 6_84 0.5117 19.46 3.262e-05 2.383 15 20
3670 NQO2 6_3 0.5116 25.24 4.071e-05 3.051 16 24Genes with highest PVE
genename region_tag susie_pip mu2 PVE z num_intron num_sqtl
380 APOPT1 14_54 0.8024 44.24 2.642e-04 7.429 6 9
3022 LRP8 1_33 1.0645 32.61 2.549e-04 -4.624 6 6
3192 MDK 11_28 0.5743 45.88 1.437e-04 7.159 1 1
241 AKT3 1_128 0.6713 34.01 1.356e-04 -6.291 6 6
1361 CRTAP 3_24 0.8430 20.01 1.343e-04 3.929 2 2
1685 DPYSL3 5_86 0.7628 23.36 1.291e-04 4.157 1 1
564 B3GAT1 11_84 0.6722 31.39 1.272e-04 -4.516 6 10
5465 THAP8 19_25 0.8114 20.21 1.261e-04 3.847 2 2
2166 FXR1 3_111 0.5532 42.91 1.221e-04 -6.873 4 4
619 BDNF 11_19 0.7481 22.63 1.203e-04 4.348 1 1
2203 GATAD2A 19_15 0.4632 45.09 9.073e-05 -6.640 4 4
5949 VPS41 7_28 0.6151 25.12 8.874e-05 -4.509 2 2
2308 GON4L 1_76 0.5783 27.63 8.773e-05 4.084 1 1
4024 PLCB2 15_14 0.6378 24.42 8.300e-05 4.470 3 4
2881 LAMA5 20_36 0.5692 32.47 8.011e-05 3.967 10 15
4326 PYROXD2 10_62 0.5608 33.32 7.427e-05 -3.718 10 11
129 ACTR1B 2_57 0.5934 22.34 7.367e-05 3.978 3 3
4280 PTK2B 8_27 0.5318 26.09 6.953e-05 4.730 2 3
5406 TCAIM 3_31 0.4480 35.10 6.170e-05 4.053 5 5
3090 MAD1L1 7_3 0.3735 62.14 5.662e-05 8.215 4 6Comparing z scores and PIPs
[1] 0.01434 genename region_tag susie_pip mu2 PVE z num_intron
3948 PGBD1 6_22 4.087e-02 155.68 9.882e-07 -13.087 2
1537 DDR1 6_25 1.261e-01 100.79 1.477e-05 11.175 3
2118 FLOT1 6_24 1.104e-01 77.49 8.920e-06 -10.944 5
692 BTN3A2 6_20 1.060e-01 88.48 4.796e-06 -10.665 4
574 BAG6 6_26 3.796e-05 160.21 1.643e-12 -10.247 5
984 CCHCR1 6_25 2.958e-02 62.23 3.774e-07 -9.378 5
2347 GPSM3 6_26 1.690e-06 118.03 3.202e-15 -9.377 1
6126 ZKSCAN3 6_22 2.955e-02 55.20 1.934e-07 -9.321 3
3706 NT5C2 10_66 3.297e-01 46.96 4.551e-05 -8.541 8
4651 RP5-874C20.8 6_22 3.391e-02 45.29 3.198e-07 -8.313 4
3090 MAD1L1 7_3 3.735e-01 62.14 5.662e-05 8.215 4
463 AS3MT 10_66 2.402e-01 44.47 2.402e-05 8.051 3
6270 ZSCAN16 6_22 2.759e-02 52.38 2.415e-07 7.468 3
380 APOPT1 14_54 8.024e-01 44.24 2.642e-04 7.429 6
3192 MDK 11_28 5.743e-01 45.88 1.437e-04 7.159 1
209 AIF1 6_26 1.311e-02 59.25 9.670e-08 -7.131 5
5564 TMEM219 16_24 3.359e-01 45.65 4.891e-05 -7.020 1
1581 DGKZ 11_28 1.388e-01 43.55 7.970e-06 -6.964 1
2643 INO80E 16_24 2.253e-01 44.02 1.928e-05 -6.917 4
2166 FXR1 3_111 5.532e-01 42.91 1.221e-04 -6.873 4
num_sqtl
3948 2
1537 3
2118 5
692 4
574 7
984 8
2347 1
6126 3
3706 11
4651 5
3090 6
463 3
6270 3
380 9
3192 1
209 5
5564 1
1581 2
2643 5
2166 4GO enrichment analysis for genes with PIP>0.5
#number of genes for gene set enrichment
length(genes)[1] 21Uploading 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
1 positive regulation of neuron projection development (GO:0010976)
2 positive regulation of cell projection organization (GO:0031346)
3 regulation of neuron projection development (GO:0010975)
4 negative regulation of neuron apoptotic process (GO:0043524)
5 positive regulation of vascular endothelial cell proliferation (GO:1905564)
6 negative regulation of neuron death (GO:1901215)
7 regulation of neuron apoptotic process (GO:0043523)
8 regulation of vascular endothelial cell proliferation (GO:1905562)
9 regulation of leukocyte chemotaxis (GO:0002688)
10 regulation of macrophage chemotaxis (GO:0010758)
11 negative regulation of ossification (GO:0030279)
12 regulation of regulatory T cell differentiation (GO:0045589)
13 activation of phospholipase C activity (GO:0007202)
14 positive regulation of protein phosphorylation (GO:0001934)
15 regulation of trans-synaptic signaling (GO:0099177)
16 regulation of actin cytoskeleton reorganization (GO:2000249)
17 regulation of filopodium assembly (GO:0051489)
18 positive regulation of protein tyrosine kinase activity (GO:0061098)
19 positive regulation of phospholipase C activity (GO:0010863)
20 positive regulation of T cell differentiation (GO:0045582)
21 negative regulation of apoptotic process (GO:0043066)
22 apoptotic process (GO:0006915)
23 positive regulation of cell-substrate adhesion (GO:0010811)
24 integrin-mediated signaling pathway (GO:0007229)
25 positive regulation of T cell activation (GO:0050870)
26 positive regulation of endothelial cell proliferation (GO:0001938)
Overlap Adjusted.P.value Genes
1 5/88 1.185e-05 BDNF;MDK;DPYSL3;PTK2B;LRP8
2 4/117 1.291e-03 BDNF;MDK;DPYSL3;PTK2B
3 4/165 3.346e-03 BDNF;MDK;DPYSL3;PTK2B
4 3/71 5.705e-03 BDNF;MDK;PTK2B
5 2/13 6.816e-03 MDK;AKT3
6 3/98 8.270e-03 BDNF;MDK;PTK2B
7 3/98 8.270e-03 BDNF;MDK;PTK2B
8 2/18 8.270e-03 MDK;AKT3
9 2/19 8.270e-03 MDK;PTK2B
10 2/22 1.004e-02 MDK;PTK2B
11 2/24 1.089e-02 MDK;PTK2B
12 2/26 1.174e-02 MDK;CD46
13 2/32 1.625e-02 BDNF;PLCB2
14 4/371 1.625e-02 FXR1;BDNF;PTK2B;LRP8
15 2/35 1.709e-02 BDNF;LRP8
16 2/37 1.791e-02 MDK;PTK2B
17 2/41 1.936e-02 FXR1;DPYSL3
18 2/42 1.936e-02 BDNF;LRP8
19 2/43 1.936e-02 BDNF;PLCB2
20 2/43 1.936e-02 MDK;CD46
21 4/485 2.938e-02 BDNF;MDK;CASP2;PTK2B
22 3/231 3.303e-02 FXR1;CASP2;PTK2B
23 2/70 4.425e-02 MDK;PTK2B
24 2/75 4.663e-02 LAMA5;PTK2B
25 2/75 4.663e-02 MDK;CD46
26 2/77 4.722e-02 MDK;AKT3
[1] "GO_Cellular_Component_2021"
[1] Term Overlap Adjusted.P.value Genes
<0 rows> (or 0-length row.names)
[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 BgRatio
3 Alcoholic Intoxication, Chronic 0.01997 4/13 268/9703
34 Profound Mental Retardation 0.01997 3/13 139/9703
41 Measles 0.01997 1/13 1/9703
44 Memory Disorders 0.01997 2/13 43/9703
45 Mental Retardation, Psychosocial 0.01997 3/13 139/9703
77 Memory impairment 0.01997 2/13 44/9703
134 Age-Related Memory Disorders 0.01997 2/13 43/9703
135 Memory Disorder, Semantic 0.01997 2/13 43/9703
136 Memory Disorder, Spatial 0.01997 2/13 43/9703
137 Memory Loss 0.01997 2/13 43/9703WebGestalt 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
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] 42#significance threshold for TWAS
print(sig_thresh)[1] 4.466#number of ctwas genes
length(ctwas_genes)[1] 4#number of TWAS genes
length(twas_genes)[1] 90#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
1361 CRTAP 3_24 0.8430 20.01 0.0001343 3.929 2 2
5465 THAP8 19_25 0.8114 20.21 0.0001261 3.847 2 2#sensitivity / recall
print(sensitivity) ctwas TWAS
0.007692 0.076923 #specificity
print(specificity) ctwas TWAS
0.9995 0.9872 #precision / PPV
print(precision) ctwas TWAS
0.2500 0.1111
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