Autism - Brain Hippocampus
sheng Qian
2021-2-6
Last updated: 2022-02-27
Checks: 6 1
Knit directory: cTWAS_analysis/
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| Rmd | 3dd5b4c | sq-96 | 2022-02-27 | update |
Weight QC
#number of imputed weights
nrow(qclist_all)[1] 11027#number of imputed weights by chromosome
table(qclist_all$chr)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1084 780 648 424 542 552 509 409 421 444 660 622 226 379 378 525
17 18 19 20 21 22
658 168 860 330 120 288 #number of imputed weights without missing variants
sum(qclist_all$nmiss==0)[1] 8830#proportion of imputed weights without missing variants
mean(qclist_all$nmiss==0)[1] 0.8008Check convergence of parameters
#estimated group prior
estimated_group_prior <- group_prior_rec[,ncol(group_prior_rec)]
names(estimated_group_prior) <- c("gene", "snp")
estimated_group_prior["snp"] <- estimated_group_prior["snp"]*thin #adjust parameter to account for thin argument
print(estimated_group_prior) gene snp
0.0122760 0.0002528 #estimated group prior variance
estimated_group_prior_var <- group_prior_var_rec[,ncol(group_prior_var_rec)]
names(estimated_group_prior_var) <- c("gene", "snp")
print(estimated_group_prior_var) gene snp
12.25 8.46 #report sample size
print(sample_size)[1] 82315#report group size
group_size <- c(nrow(ctwas_gene_res), n_snps)
print(group_size)[1] 11027 7573890#estimated group PVE
estimated_group_pve <- estimated_group_prior_var*estimated_group_prior*group_size/sample_size #check PVE calculation
names(estimated_group_pve) <- c("gene", "snp")
print(estimated_group_pve) gene snp
0.02014 0.19680 #compare sum(PIP*mu2/sample_size) with above PVE calculation
c(sum(ctwas_gene_res$PVE),sum(ctwas_snp_res$PVE))[1] 0.1542 1.5603Genes with highest PIPs
genename region_tag susie_pip mu2 PVE z num_eqtl
3391 CRHR1 17_27 1.0000 4090.65 0.0496950 3.362 1
10755 ZKSCAN8 6_22 0.9899 1791.68 0.0215453 5.406 2
10687 ZNF823 19_10 0.9820 30.13 0.0003594 5.455 1
8759 MAP3K11 11_36 0.8843 23.83 0.0002560 -4.544 1
6779 ZSCAN12 6_22 0.8645 846.93 0.0088944 10.940 1
11759 HIST1H2BN 6_21 0.8628 95.15 0.0009973 10.773 1
12742 TBC1D29 17_18 0.8469 22.50 0.0002315 4.578 2
1516 TTLL1 22_18 0.7990 23.82 0.0002313 -4.667 2
7929 ENDOG 9_66 0.7967 23.37 0.0002262 4.806 2
6084 ARFGAP2 11_29 0.7965 25.00 0.0002419 4.740 1
3607 BHLHE41 12_18 0.7912 22.15 0.0002129 -4.024 1
6202 PLBD2 12_68 0.7808 20.44 0.0001938 3.986 1
11532 LINC00390 13_17 0.7638 20.77 0.0001927 -4.166 1
8652 FUT9 6_65 0.7578 30.23 0.0002783 5.427 1
436 ARID1B 6_102 0.7300 21.88 0.0001940 -3.907 1
10075 TMEM222 1_19 0.7129 23.45 0.0002031 3.902 1
104 ELAC2 17_11 0.6763 23.15 0.0001902 4.227 1
11534 LINC00606 3_8 0.6693 23.42 0.0001904 -3.964 1
2469 TBC1D19 4_22 0.6633 21.39 0.0001723 4.146 1
10925 LIN28B-AS1 6_70 0.6508 23.57 0.0001863 -4.651 1Genes with largest effect sizes
genename region_tag susie_pip mu2 PVE z num_eqtl
3391 CRHR1 17_27 1.000e+00 4090.65 4.970e-02 3.3623 1
10755 ZKSCAN8 6_22 9.899e-01 1791.68 2.155e-02 5.4057 2
10581 ZNF165 6_22 0.000e+00 1289.20 0.000e+00 4.3541 2
10546 ZSCAN26 6_22 7.559e-12 1221.35 1.121e-13 8.3004 2
10362 ZKSCAN3 6_22 0.000e+00 903.12 0.000e+00 6.5137 1
6779 ZSCAN12 6_22 8.645e-01 846.93 8.894e-03 10.9401 1
6833 ARHGAP27 17_27 0.000e+00 735.33 0.000e+00 0.6410 2
11810 ZSCAN31 6_22 0.000e+00 693.84 0.000e+00 -3.0550 2
10383 HLA-DRB1 6_27 0.000e+00 487.58 0.000e+00 4.3158 1
10219 ZSCAN23 6_22 0.000e+00 295.33 0.000e+00 -6.9089 1
12006 HLA-DMB 6_27 0.000e+00 281.88 0.000e+00 -8.0544 1
10782 HLA-DRB5 6_27 0.000e+00 250.39 0.000e+00 2.9680 1
9350 HLA-DQB1 6_27 0.000e+00 232.89 0.000e+00 1.0000 1
10106 HEXIM1 17_27 0.000e+00 142.54 0.000e+00 -3.3281 1
4828 NMT1 17_27 0.000e+00 138.82 0.000e+00 2.4473 2
9374 RPRML 17_27 0.000e+00 108.90 0.000e+00 0.4344 2
4944 PGBD1 6_22 0.000e+00 104.14 0.000e+00 1.6011 1
11759 HIST1H2BN 6_21 8.628e-01 95.15 9.973e-04 10.7729 1
10966 COL11A2 6_27 0.000e+00 86.40 0.000e+00 4.3742 2
2357 GOSR2 17_27 0.000e+00 78.76 0.000e+00 -2.5096 1Genes with highest PVE
genename region_tag susie_pip mu2 PVE z num_eqtl
3391 CRHR1 17_27 1.0000 4090.65 0.0496950 3.362 1
10755 ZKSCAN8 6_22 0.9899 1791.68 0.0215453 5.406 2
6779 ZSCAN12 6_22 0.8645 846.93 0.0088944 10.940 1
11759 HIST1H2BN 6_21 0.8628 95.15 0.0009973 10.773 1
10687 ZNF823 19_10 0.9820 30.13 0.0003594 5.455 1
8652 FUT9 6_65 0.7578 30.23 0.0002783 5.427 1
8759 MAP3K11 11_36 0.8843 23.83 0.0002560 -4.544 1
910 NT5C2 10_66 0.5235 40.16 0.0002554 -7.489 2
8275 INO80E 16_24 0.5100 40.11 0.0002485 6.350 1
1736 PPP1R16B 20_23 0.5709 35.72 0.0002477 6.091 1
6084 ARFGAP2 11_29 0.7965 25.00 0.0002419 4.740 1
12742 TBC1D29 17_18 0.8469 22.50 0.0002315 4.578 2
1516 TTLL1 22_18 0.7990 23.82 0.0002313 -4.667 2
7929 ENDOG 9_66 0.7967 23.37 0.0002262 4.806 2
12176 YJEFN3 19_15 0.5684 32.08 0.0002215 -5.736 1
2535 MDK 11_28 0.4657 39.04 0.0002209 -6.357 1
3607 BHLHE41 12_18 0.7912 22.15 0.0002129 -4.024 1
626 SNAP91 6_57 0.5517 30.94 0.0002074 5.814 1
10075 TMEM222 1_19 0.7129 23.45 0.0002031 3.902 1
436 ARID1B 6_102 0.7300 21.88 0.0001940 -3.907 1Genes with largest z scores
genename region_tag susie_pip mu2 PVE z num_eqtl
6779 ZSCAN12 6_22 8.645e-01 846.93 8.894e-03 10.940 1
11759 HIST1H2BN 6_21 8.628e-01 95.15 9.973e-04 10.773 1
12628 CTA-14H9.5 6_20 2.067e-02 67.63 1.698e-05 9.082 1
13065 RP1-86C11.7 6_21 1.016e-01 74.47 9.190e-05 -9.033 1
10071 BTN3A2 6_20 1.858e-02 65.31 1.474e-05 8.998 2
10546 ZSCAN26 6_22 7.559e-12 1221.35 1.121e-13 8.300 2
12006 HLA-DMB 6_27 0.000e+00 281.88 0.000e+00 -8.054 1
9448 HIST1H2BC 6_20 2.125e-02 52.71 1.361e-05 -8.028 1
2719 TRIM38 6_20 1.646e-02 47.14 9.423e-06 -7.700 2
6064 CNNM2 10_66 8.581e-02 37.30 3.889e-05 -7.691 1
910 NT5C2 10_66 5.235e-01 40.16 2.554e-04 -7.489 2
10219 ZSCAN23 6_22 0.000e+00 295.33 0.000e+00 -6.909 1
10362 ZKSCAN3 6_22 0.000e+00 903.12 0.000e+00 6.514 1
6186 ABCB9 12_75 8.133e-03 39.30 3.883e-06 6.404 1
2535 MDK 11_28 4.657e-01 39.04 2.209e-04 -6.357 1
8275 INO80E 16_24 5.100e-01 40.11 2.485e-04 6.350 1
2981 KCNJ13 2_137 2.463e-01 35.54 1.064e-04 6.333 1
12375 APOPT1 14_54 3.889e-02 35.96 1.699e-05 -6.260 2
10290 DPYD 1_60 1.148e-02 36.66 5.112e-06 -6.222 1
6146 TAOK2 16_24 2.213e-01 37.86 1.018e-04 6.189 1Comparing z scores and PIPs
[1] 0.006711 genename region_tag susie_pip mu2 PVE z num_eqtl
6779 ZSCAN12 6_22 8.645e-01 846.93 8.894e-03 10.940 1
11759 HIST1H2BN 6_21 8.628e-01 95.15 9.973e-04 10.773 1
12628 CTA-14H9.5 6_20 2.067e-02 67.63 1.698e-05 9.082 1
13065 RP1-86C11.7 6_21 1.016e-01 74.47 9.190e-05 -9.033 1
10071 BTN3A2 6_20 1.858e-02 65.31 1.474e-05 8.998 2
10546 ZSCAN26 6_22 7.559e-12 1221.35 1.121e-13 8.300 2
12006 HLA-DMB 6_27 0.000e+00 281.88 0.000e+00 -8.054 1
9448 HIST1H2BC 6_20 2.125e-02 52.71 1.361e-05 -8.028 1
2719 TRIM38 6_20 1.646e-02 47.14 9.423e-06 -7.700 2
6064 CNNM2 10_66 8.581e-02 37.30 3.889e-05 -7.691 1
910 NT5C2 10_66 5.235e-01 40.16 2.554e-04 -7.489 2
10219 ZSCAN23 6_22 0.000e+00 295.33 0.000e+00 -6.909 1
10362 ZKSCAN3 6_22 0.000e+00 903.12 0.000e+00 6.514 1
6186 ABCB9 12_75 8.133e-03 39.30 3.883e-06 6.404 1
2535 MDK 11_28 4.657e-01 39.04 2.209e-04 -6.357 1
8275 INO80E 16_24 5.100e-01 40.11 2.485e-04 6.350 1
2981 KCNJ13 2_137 2.463e-01 35.54 1.064e-04 6.333 1
12375 APOPT1 14_54 3.889e-02 35.96 1.699e-05 -6.260 2
10290 DPYD 1_60 1.148e-02 36.66 5.112e-06 -6.222 1
6146 TAOK2 16_24 2.213e-01 37.86 1.018e-04 6.189 1GO enrichment analysis for genes with PIP>0.5
#number of genes for gene set enrichment
length(genes)[1] 32Uploading 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 regulation of plasma membrane bounded cell projection assembly (GO:0120032)
Overlap Adjusted.P.value Genes
1 3/70 0.04393 PPP1R16B;TBC1D19;TBC1D15
[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
72 PROSTATE CANCER, HEREDITARY, 2 0.02144 1/8 1/9703
74 COMBINED OXIDATIVE PHOSPHORYLATION DEFICIENCY 17 0.02144 1/8 1/9703
76 SPASTIC PARAPLEGIA 45, AUTOSOMAL RECESSIVE 0.02144 1/8 1/9703
24 Pain, Postoperative 0.02572 1/8 2/9703
70 CHROMOSOME 6q24-q25 DELETION SYNDROME 0.02572 1/8 2/9703
51 Long Sleeper Syndrome 0.03744 1/8 7/9703
52 Short Sleeper Syndrome 0.03744 1/8 7/9703
53 Sleep-Related Neurogenic Tachypnea 0.03744 1/8 7/9703
54 Subwakefullness Syndrome 0.03744 1/8 7/9703
55 Sleep Disorders 0.03744 1/8 7/9703WebGestalt enrichment analysis for genes with PIP>0.5
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] 41#number of genes in known annotations with imputed expression
print(sum(known_annotations %in% ctwas_gene_res$genename))[1] 23#significance threshold for TWAS
print(sig_thresh)[1] 4.585#number of ctwas genes
length(ctwas_genes)[1] 7#number of TWAS genes
length(twas_genes)[1] 74#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_eqtl
8759 MAP3K11 11_36 0.8843 23.83 0.0002560 -4.544 1
12742 TBC1D29 17_18 0.8469 22.50 0.0002315 4.578 2
3391 CRHR1 17_27 1.0000 4090.65 0.0496950 3.362 1#sensitivity / recall
print(sensitivity)ctwas TWAS
0 0 #specificity
print(specificity) ctwas TWAS
0.9994 0.9933 #precision / PPV
print(precision)ctwas TWAS
0 0 
sessionInfo()R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.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_1.3.1 forcats_0.5.1 stringr_1.4.0 dplyr_1.0.7
[5] purrr_0.3.4 readr_2.1.1 tidyr_1.1.4 tidyverse_1.3.1
[9] tibble_3.1.6 WebGestaltR_0.4.4 disgenet2r_0.99.2 enrichR_3.0
[13] cowplot_1.0.0 ggplot2_3.3.5 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] fs_1.5.2 lubridate_1.8.0 bit64_4.0.5 doParallel_1.0.17
[5] httr_1.4.2 rprojroot_2.0.2 tools_3.6.1 backports_1.4.1
[9] doRNG_1.8.2 utf8_1.2.2 R6_2.5.1 vipor_0.4.5
[13] DBI_1.1.2 colorspace_2.0-2 withr_2.4.3 ggrastr_1.0.1
[17] tidyselect_1.1.1 bit_4.0.4 curl_4.3.2 compiler_3.6.1
[21] git2r_0.26.1 rvest_1.0.2 cli_3.1.0 Cairo_1.5-12.2
[25] xml2_1.3.3 labeling_0.4.2 scales_1.1.1 apcluster_1.4.8
[29] digest_0.6.29 rmarkdown_2.11 svglite_1.2.2 pkgconfig_2.0.3
[33] htmltools_0.5.2 dbplyr_2.1.1 fastmap_1.1.0 highr_0.9
[37] rlang_1.0.1 rstudioapi_0.13 RSQLite_2.2.8 jquerylib_0.1.4
[41] farver_2.1.0 generics_0.1.1 jsonlite_1.7.2 vroom_1.5.7
[45] magrittr_2.0.2 Matrix_1.2-18 ggbeeswarm_0.6.0 Rcpp_1.0.8
[49] munsell_0.5.0 fansi_1.0.2 gdtools_0.1.9 lifecycle_1.0.1
[53] stringi_1.7.6 whisker_0.3-2 yaml_2.2.1 plyr_1.8.6
[57] grid_3.6.1 blob_1.2.2 ggrepel_0.9.1 parallel_3.6.1
[61] promises_1.0.1 crayon_1.5.0 lattice_0.20-38 haven_2.4.3
[65] hms_1.1.1 knitr_1.36 pillar_1.6.4 igraph_1.2.10
[69] rjson_0.2.20 rngtools_1.5.2 reshape2_1.4.4 codetools_0.2-16
[73] reprex_2.0.1 glue_1.6.2 evaluate_0.14 data.table_1.14.2
[77] modelr_0.1.8 vctrs_0.3.8 tzdb_0.2.0 httpuv_1.5.1
[81] foreach_1.5.2 cellranger_1.1.0 gtable_0.3.0 assertthat_0.2.1
[85] cachem_1.0.6 xfun_0.29 broom_0.7.10 later_0.8.0
[89] iterators_1.0.14 beeswarm_0.2.3 memoise_2.0.1 ellipsis_0.3.2