SCZ 2018 - Brain_Hypothalamus
sheng Qian
2021-2-6
Last updated: 2022-05-12
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] 19902#number of imputed weights by chromosome
table(qclist_all$chr)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1843 1406 1208 781 846 1042 1147 677 814 921 1170 1073 396 705 657 781
17 18 19 20 21 22
1382 282 1439 658 36 638 #number of imputed weights without missing variants
sum(qclist_all$nmiss==0)[1] 17601#proportion of imputed weights without missing variants
mean(qclist_all$nmiss==0)[1] 0.8844finish
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
gene snp
0.0083920 0.0003085 gene snp
11.94 10.24 [1] 105318[1] 7513 6309950 gene snp
0.007149 0.189243 [1] 0.01859 1.05816Genes with highest PIPs
genename region_tag susie_pip mu2 PVE z num_intron num_sqtl
5103 R3HDM2 12_36 1.1229 43.52 0.0004828 -6.634 4 4
2376 FEZF1 7_74 1.0238 24.62 0.0002438 -4.812 3 3
3363 LINC00320 21_6 0.9653 29.24 0.0002429 -5.336 5 5
3476 LRP8 1_33 0.9575 23.82 0.0002046 4.654 3 4
2562 GIGYF2 2_137 0.9417 56.62 0.0004418 8.128 3 3
258 AKT3 1_128 0.9409 34.79 0.0002743 -6.291 7 7
4303 NRXN2 11_36 0.9073 24.81 0.0001918 4.723 3 3
7272 ZIC4 3_91 0.9031 23.46 0.0001755 -4.221 3 4
6428 THAP8 19_25 0.8792 19.47 0.0001426 3.847 2 2
5062 PTPRF 1_27 0.8792 37.18 0.0002644 6.680 4 4
1533 CRTAP 3_24 0.8764 19.92 0.0001445 3.929 2 2
119 ACTR1B 2_57 0.8316 19.24 0.0001263 -3.978 4 4
2561 GIGYF1 7_63 0.8088 28.55 0.0001764 -5.266 3 3
3920 MRPS33 7_87 0.7742 23.44 0.0001275 -4.304 4 5
6769 TSNARE1 8_93 0.7719 28.75 0.0001581 5.782 7 10
1894 DPYSL3 5_86 0.7459 22.30 0.0001178 4.157 1 1
2175 ETF1 5_82 0.7438 33.82 0.0001776 6.112 1 1
5661 SF3B1 2_117 0.7398 45.62 0.0002320 7.053 2 2
6959 UQCRC2 16_19 0.7381 22.09 0.0001143 4.716 2 2
1759 DHPS 19_10 0.7270 24.40 0.0001225 -4.396 1 1Genes with highest PVE
genename region_tag susie_pip mu2 PVE z num_intron num_sqtl
5103 R3HDM2 12_36 1.1229 43.52 0.0004828 -6.634 4 4
2562 GIGYF2 2_137 0.9417 56.62 0.0004418 8.128 3 3
258 AKT3 1_128 0.9409 34.79 0.0002743 -6.291 7 7
5062 PTPRF 1_27 0.8792 37.18 0.0002644 6.680 4 4
2376 FEZF1 7_74 1.0238 24.62 0.0002438 -4.812 3 3
3363 LINC00320 21_6 0.9653 29.24 0.0002429 -5.336 5 5
5661 SF3B1 2_117 0.7398 45.62 0.0002320 7.053 2 2
1403 COA8 14_54 0.6940 46.11 0.0002066 7.429 4 7
3476 LRP8 1_33 0.9575 23.82 0.0002046 4.654 3 4
4303 NRXN2 11_36 0.9073 24.81 0.0001918 4.723 3 3
2175 ETF1 5_82 0.7438 33.82 0.0001776 6.112 1 1
2561 GIGYF1 7_63 0.8088 28.55 0.0001764 -5.266 3 3
7272 ZIC4 3_91 0.9031 23.46 0.0001755 -4.221 3 4
6769 TSNARE1 8_93 0.7719 28.75 0.0001581 5.782 7 10
6309 TAOK2 16_24 0.6069 47.40 0.0001572 -7.024 5 5
1533 CRTAP 3_24 0.8764 19.92 0.0001445 3.929 2 2
6428 THAP8 19_25 0.8792 19.47 0.0001426 3.847 2 2
3920 MRPS33 7_87 0.7742 23.44 0.0001275 -4.304 4 5
119 ACTR1B 2_57 0.8316 19.24 0.0001263 -3.978 4 4
5064 PTPRK 6_85 0.6805 28.67 0.0001246 5.059 2 2Comparing z scores and PIPs
[1] 0.01784 genename region_tag susie_pip mu2 PVE z num_intron
4615 PGBD1 6_22 4.933e-02 161.09 1.444e-06 -13.087 2
7012 VARS1 6_26 8.163e-05 217.29 1.375e-11 -11.548 1
410 APOM 6_26 8.321e-05 217.08 1.427e-11 -11.541 1
1695 DDR1 6_25 1.495e-01 101.78 2.106e-05 11.175 2
7013 VARS2 6_25 1.018e-01 100.66 9.907e-06 -11.137 1
865 C6orf136 6_24 9.472e-02 80.92 6.894e-06 -11.031 2
2405 FLOT1 6_24 2.537e-01 79.57 4.851e-05 10.981 7
760 BTN3A2 6_20 1.183e-01 91.37 4.454e-06 -10.659 6
645 BAG6 6_26 3.211e-05 166.08 1.378e-12 10.247 8
5371 RNF5 6_26 2.893e-05 150.34 1.195e-12 -10.045 1
1074 CCHCR1 6_25 5.652e-02 66.51 1.192e-06 9.508 9
2676 GPSM3 6_26 1.971e-06 122.29 4.509e-15 -9.377 1
4323 NT5C2 10_66 4.641e-01 48.79 9.244e-05 -8.511 8
7505 ZSCAN26 6_22 3.788e-02 46.81 4.314e-07 8.304 4
2562 GIGYF2 2_137 9.417e-01 56.62 4.418e-04 8.128 3
3935 MSH5 6_26 1.908e-05 72.41 1.864e-13 7.892 3
786 C12orf65 12_75 2.009e-01 55.60 2.131e-05 -7.754 1
7274 ZKSCAN3 6_22 2.099e-02 36.54 8.960e-08 -7.740 2
759 BTN3A1 6_20 7.314e-02 47.48 7.925e-07 7.490 5
7501 ZSCAN16-AS1 6_22 8.557e-03 54.06 3.759e-08 -7.460 1
num_sqtl
4615 3
7012 1
410 1
1695 2
7013 1
865 2
2405 8
760 7
645 11
5371 1
1074 13
2676 1
4323 12
7505 5
2562 3
3935 3
786 1
7274 2
759 5
7501 1GO enrichment analysis for genes with PIP>0.5
#number of genes for gene set enrichment
length(genes)[1] 66Uploading 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
32 Measles 0.02501 1/31
48 Schizophrenia 0.02501 10/31
54 Electroencephalogram abnormal 0.02501 1/31
60 Congenital absent nipple 0.02501 1/31
97 Congenital absence of breast with absent nipple 0.02501 1/31
127 Sporadic Breast Carcinoma 0.02501 1/31
130 Primary peritoneal carcinoma 0.02501 1/31
136 Osteogenesis Imperfecta Type VII 0.02501 1/31
137 Familial encephalopathy with neuroserpin inclusion bodies 0.02501 1/31
142 BREAST-OVARIAN CANCER, FAMILIAL, SUSCEPTIBILITY TO, 1 0.02501 1/31
BgRatio
32 1/9703
48 883/9703
54 1/9703
60 1/9703
97 1/9703
127 1/9703
130 1/9703
136 1/9703
137 1/9703
142 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: 22 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] 52#significance threshold for TWAS
print(sig_thresh)[1] 4.504#number of ctwas genes
length(ctwas_genes)[1] 13#number of TWAS genes
length(twas_genes)[1] 134#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
119 ACTR1B 2_57 0.8316 19.24 0.0001263 -3.978 4 4
1533 CRTAP 3_24 0.8764 19.92 0.0001445 3.929 2 2
6428 THAP8 19_25 0.8792 19.47 0.0001426 3.847 2 2
7272 ZIC4 3_91 0.9031 23.46 0.0001755 -4.221 3 4#sensitivity / recall
print(sensitivity) ctwas TWAS
0.03846 0.13077 #specificity
print(specificity) ctwas TWAS
0.9989 0.9843 #precision / PPV
print(precision) ctwas TWAS
0.3846 0.1269
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_1.20 workflowr_1.6.2
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 curl_4.3.2 compiler_4.1.0 git2r_0.28.0
[21] rvest_1.0.0 cli_3.0.0 Cairo_1.5-15 xml2_1.3.2
[25] labeling_0.4.2 sass_0.4.0 scales_1.1.1 systemfonts_1.0.4
[29] apcluster_1.4.9 digest_0.6.27 rmarkdown_2.9 svglite_2.0.0
[33] pkgconfig_2.0.3 htmltools_0.5.1.1 dbplyr_2.1.1 highr_0.9
[37] rlang_1.0.2 rstudioapi_0.13 jquerylib_0.1.4 farver_2.1.0
[41] generics_0.1.0 jsonlite_1.7.2 magrittr_2.0.1 Matrix_1.3-3
[45] ggbeeswarm_0.6.0 Rcpp_1.0.7 munsell_0.5.0 fansi_0.5.0
[49] lifecycle_1.0.0 stringi_1.6.2 whisker_0.4 yaml_2.2.1
[53] plyr_1.8.6 grid_4.1.0 ggrepel_0.9.1 parallel_4.1.0
[57] promises_1.2.0.1 crayon_1.4.1 lattice_0.20-44 haven_2.4.1
[61] hms_1.1.0 knitr_1.33 pillar_1.7.0 igraph_1.2.6
[65] rjson_0.2.20 rngtools_1.5 reshape2_1.4.4 codetools_0.2-18
[69] reprex_2.0.0 glue_1.4.2 evaluate_0.14 data.table_1.14.0
[73] modelr_0.1.8 png_0.1-7 vctrs_0.3.8 httpuv_1.6.1
[77] foreach_1.5.1 cellranger_1.1.0 gtable_0.3.0 assertthat_0.2.1
[81] xfun_0.24 broom_0.7.8 later_1.2.0 iterators_1.0.13
[85] beeswarm_0.4.0 ellipsis_0.3.2