SCZ 2018 - Brain_Cerebellar_Hemisphere
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] 26564#number of imputed weights by chromosome
table(qclist_all$chr)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
2520 1814 1594 973 1137 1377 1526 911 1106 1166 1579 1419 520 921 928 1179
17 18 19 20 21 22
1880 325 1895 891 51 852 #number of imputed weights without missing variants
sum(qclist_all$nmiss==0)[1] 23201#proportion of imputed weights without missing variants
mean(qclist_all$nmiss==0)[1] 0.8734INFO: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
0.0103642 0.0002912 gene snp
12.00 10.12 [1] 105318[1] 7860 6309950 gene snp
0.009283 0.176540 [1] 0.03488 1.05335Genes with highest PIPs
genename region_tag susie_pip mu2 PVE z num_intron num_sqtl
6205 SLC8B1 12_68 1.5477 28.59 0.0005738 -4.047 11 12
3667 LRP8 1_33 1.2607 32.55 0.0003761 4.820 11 11
7425 WDR27 6_111 1.1795 17.37 0.0001185 2.338 30 41
2396 FAM177A1 14_9 1.1555 24.30 0.0002576 -4.872 12 13
2719 GIGYF2 2_137 1.0940 56.96 0.0005633 -8.128 6 6
5293 R3HDM2 12_36 1.0731 43.83 0.0004526 6.634 9 11
4759 PDXDC1 16_15 1.0670 29.62 0.0001711 3.879 23 25
3651 LPCAT4 15_10 0.9950 25.36 0.0002297 4.892 3 4
2718 GIGYF1 7_62 0.9927 26.42 0.0002425 -5.266 5 5
1156 CCDC57 17_47 0.9837 18.98 0.0001239 -3.061 34 44
842 BUB1B-PAK6 15_14 0.9466 29.86 0.0002496 -5.588 2 2
3512 LAMA5 20_37 0.9462 28.70 0.0001979 -4.211 25 32
151 ACTR1B 2_57 0.9438 19.16 0.0001576 3.978 9 9
4686 PATJ 1_39 0.9400 22.53 0.0001571 2.798 15 17
1039 CAMKK2 12_74 0.9338 35.78 0.0002086 4.159 6 8
5994 SF3B1 2_117 0.9204 45.85 0.0003612 -7.053 3 3
4104 MRPS33 7_87 0.9200 20.70 0.0001602 -4.304 5 5
1478 CNOT1 16_31 0.9167 35.98 0.0002567 6.282 10 11
6749 THAP8 19_25 0.9103 19.03 0.0001497 3.847 2 2
5281 PYROXD2 10_62 0.9087 21.98 0.0001517 -3.852 9 10
4549 NUP50 22_20 0.8804 18.64 0.0001329 -3.850 5 5
6287 SNRPA1 15_50 0.8782 21.98 0.0001513 -3.913 5 6
6009 SGCE 7_58 0.8780 20.72 0.0001455 4.413 6 6
294 AKT3 1_128 0.8712 35.12 0.0002321 6.266 6 6
1275 CECR2 22_2 0.8629 18.61 0.0001295 -3.928 4 4
4513 NTRK3 15_41 0.8602 24.09 0.0001557 4.457 3 3
1754 CUL9 6_33 0.8557 31.85 0.0001747 4.961 11 12
6940 TNK2 3_120 0.8483 27.71 0.0001251 3.409 16 16
7078 TSNARE1 8_93 0.8348 34.12 0.0001825 6.364 10 10
680 B3GAT1 11_84 0.8323 23.80 0.0001477 4.394 4 6
7567 ZDHHC20 13_2 0.8099 25.00 0.0001495 -4.832 3 4
1631 CRTAP 3_24 0.8018 20.88 0.0001249 3.929 2 2Genes with highest PVE
genename region_tag susie_pip mu2 PVE z num_intron
456 APOM 6_26 0.4404 626.01 0.0011520 11.590 3
7339 VARS 6_26 0.3832 628.56 0.0008763 -11.620 2
837 BTN3A1 6_20 0.7245 145.15 0.0006369 13.091 7
6205 SLC8B1 12_68 1.5477 28.59 0.0005738 -4.047 11
2719 GIGYF2 2_137 1.0940 56.96 0.0005633 -8.128 6
5293 R3HDM2 12_36 1.0731 43.83 0.0004526 6.634 9
3667 LRP8 1_33 1.2607 32.55 0.0003761 4.820 11
5994 SF3B1 2_117 0.9204 45.85 0.0003612 -7.053 3
2396 FAM177A1 14_9 1.1555 24.30 0.0002576 -4.872 12
1478 CNOT1 16_31 0.9167 35.98 0.0002567 6.282 10
842 BUB1B-PAK6 15_14 0.9466 29.86 0.0002496 -5.588 2
2718 GIGYF1 7_62 0.9927 26.42 0.0002425 -5.266 5
294 AKT3 1_128 0.8712 35.12 0.0002321 6.266 6
3651 LPCAT4 15_10 0.9950 25.36 0.0002297 4.892 3
1039 CAMKK2 12_74 0.9338 35.78 0.0002086 4.159 6
3512 LAMA5 20_37 0.9462 28.70 0.0001979 -4.211 25
7005 TRANK1 3_27 0.7567 38.76 0.0001973 -6.365 6
7078 TSNARE1 8_93 0.8348 34.12 0.0001825 6.364 10
1754 CUL9 6_33 0.8557 31.85 0.0001747 4.961 11
4759 PDXDC1 16_15 1.0670 29.62 0.0001711 3.879 23
num_sqtl
456 4
7339 2
837 8
6205 12
2719 6
5293 11
3667 11
5994 3
2396 13
1478 11
842 2
2718 5
294 6
3651 4
1039 8
3512 32
7005 6
7078 10
1754 12
4759 25Comparing z scores and PIPs
[1] 0.02176 genename region_tag susie_pip mu2 PVE z num_intron num_sqtl
7606 ZKSCAN3 6_22 6.184e-02 160.21 3.269e-06 -13.135 4 4
837 BTN3A1 6_20 7.245e-01 145.15 6.369e-04 13.091 7 8
4797 PGBD1 6_22 1.027e-01 159.13 7.726e-06 -13.087 5 7
7339 VARS 6_26 3.832e-01 628.56 8.763e-04 -11.620 2 2
456 APOM 6_26 4.404e-01 626.01 1.152e-03 11.590 3 4
1851 DDR1 6_25 3.515e-01 101.78 1.165e-04 -11.175 4 4
964 C6orf136 6_24 1.205e-01 80.18 1.105e-05 -11.031 2 2
2559 FLOT1 6_24 3.515e-01 78.83 9.198e-05 10.981 8 8
838 BTN3A2 6_20 1.534e-01 94.90 1.064e-05 -10.743 5 7
1781 CYP21A2 6_26 5.976e-06 607.99 2.062e-13 -10.513 1 2
699 BAG6 6_26 5.908e-09 500.57 1.659e-19 10.247 9 9
835 BTN2A1 6_20 1.490e-01 84.19 6.335e-06 10.110 7 7
5104 PPT2 6_26 5.412e-12 466.36 1.297e-25 10.061 7 9
2138 EGFL8 6_26 4.315e-12 465.72 8.227e-26 10.036 6 7
5165 PRRT1 6_26 3.762e-12 464.63 6.243e-26 -10.018 1 1
2850 GPSM3 6_26 2.356e-13 416.63 2.196e-28 -9.377 2 2
1176 CCHCR1 6_25 9.102e-02 59.77 1.948e-06 -9.032 11 18
6952 TNXB 6_26 2.108e-13 454.39 1.918e-28 9.001 4 5
3026 HLA-DMA 6_27 1.797e-01 70.57 1.141e-05 8.860 5 6
7849 ZSCAN23 6_22 1.294e-02 46.07 7.324e-08 -8.541 1 1GO enrichment analysis for genes with PIP>0.5
#number of genes for gene set enrichment
length(genes)[1] 135Uploading 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"
[1] Term Overlap Adjusted.P.value Genes
<0 rows> (or 0-length row.names)
[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
13 Balo's Concentric Sclerosis 0.05674 1/84 1/9703
40 Diffuse Cerebral Sclerosis of Schilder 0.05674 1/84 1/9703
90 Profound Mental Retardation 0.05674 5/84 139/9703
100 Acute monocytic leukemia 0.05674 3/84 26/9703
101 Leukemia, Myelocytic, Acute 0.05674 6/84 173/9703
112 Measles 0.05674 1/84 1/9703
116 Mental Retardation, Psychosocial 0.05674 5/84 139/9703
132 Nicotine Dependence 0.05674 2/84 14/9703
154 Schizophrenia 0.05674 17/84 883/9703
158 Status Epilepticus 0.05674 4/84 68/9703WebGestalt 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...
description size overlap FDR database
1 Bipolar Disorder 136 13 0.001345 disease_GLAD4U
2 Schizophrenia 165 13 0.005978 disease_GLAD4U
3 Mental Disorders 247 15 0.017847 disease_GLAD4U
userId
1 AS3MT;BDNF;CAMKK2;DLG1;GABBR2;ITIH4;NT5C2;NTRK3;SDCCAG8;SYNE1;TCF4;TRANK1;TSNARE1
2 AHI1;AS3MT;BDNF;CAMKK2;DLG1;ITIH4;NT5C2;NTRK3;SDCCAG8;SYNE1;TCF4;TRANK1;TSNARE1
3 ADAM10;AHI1;AS3MT;BDNF;GABBR2;ITIH4;LRP8;MEF2C;NT5C2;NTRK3;SGCE;SYNE1;TCF4;TRANK1;TSNARE1PIP Manhattan Plot
Warning: Removed 2 rows containing missing values (geom_point).
Warning: Removed 2 rows containing missing values (geom_point).Warning: Removed 2 rows containing missing values (geom_label_repel).Warning: ggrepel: 93 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] 59#significance threshold for TWAS
print(sig_thresh)[1] 4.514#number of ctwas genes
length(ctwas_genes)[1] 32#number of TWAS genes
length(twas_genes)[1] 171#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
151 ACTR1B 2_57 0.9438 19.16 0.0001576 3.978 9 9
680 B3GAT1 11_84 0.8323 23.80 0.0001477 4.394 4 6
1039 CAMKK2 12_74 0.9338 35.78 0.0002086 4.159 6 8
1156 CCDC57 17_47 0.9837 18.98 0.0001239 -3.061 34 44
1275 CECR2 22_2 0.8629 18.61 0.0001295 -3.928 4 4
1631 CRTAP 3_24 0.8018 20.88 0.0001249 3.929 2 2
3512 LAMA5 20_37 0.9462 28.70 0.0001979 -4.211 25 32
4104 MRPS33 7_87 0.9200 20.70 0.0001602 -4.304 5 5
4513 NTRK3 15_41 0.8602 24.09 0.0001557 4.457 3 3
4549 NUP50 22_20 0.8804 18.64 0.0001329 -3.850 5 5
4686 PATJ 1_39 0.9400 22.53 0.0001571 2.798 15 17
4759 PDXDC1 16_15 1.0670 29.62 0.0001711 3.879 23 25
5281 PYROXD2 10_62 0.9087 21.98 0.0001517 -3.852 9 10
6009 SGCE 7_58 0.8780 20.72 0.0001455 4.413 6 6
6205 SLC8B1 12_68 1.5477 28.59 0.0005738 -4.047 11 12
6287 SNRPA1 15_50 0.8782 21.98 0.0001513 -3.913 5 6
6749 THAP8 19_25 0.9103 19.03 0.0001497 3.847 2 2
6940 TNK2 3_120 0.8483 27.71 0.0001251 3.409 16 16
7425 WDR27 6_111 1.1795 17.37 0.0001185 2.338 30 41#sensitivity / recall
print(sensitivity) ctwas TWAS
0.05385 0.13077 #specificity
print(specificity) ctwas TWAS
0.9968 0.9803 #precision / PPV
print(precision) ctwas TWAS
0.21875 0.09942
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