WhiteBlood - WholeBlood gene expression
sheng Qian
2023-2-1
Last updated: 2023-02-03
Checks: 5 2
Knit directory: cTWAS_analysis/
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Weight QC
#number of imputed weights
nrow(qclist_all)[1] 11095#number of imputed weights by chromosome
table(qclist_all$chr)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1129 747 624 400 479 621 560 383 404 430 682 652 192 362 331 551
17 18 19 20 21 22
725 159 911 313 130 310 #number of imputed weights without missing variants
sum(qclist_all$nmiss==0)[1] 8463#proportion of imputed weights without missing variants
mean(qclist_all$nmiss==0)[1] 0.7628Check convergence of parameters
| Version | Author | Date |
|---|---|---|
| 9b01dad | sq-96 | 2023-02-01 |
#estimated group prior
estimated_group_prior <- group_prior_rec[,ncol(group_prior_rec)]
names(estimated_group_prior) <- c("gene", "snp")
estimated_group_prior["snp"] <- estimated_group_prior["snp"]*thin #adjust parameter to account for thin argument
print(estimated_group_prior) gene snp
0.021865 0.000204 #estimated group prior variance
estimated_group_prior_var <- group_prior_var_rec[,ncol(group_prior_var_rec)]
names(estimated_group_prior_var) <- c("gene", "snp")
print(estimated_group_prior_var) gene snp
19.48 17.47 #report sample size
print(sample_size)[1] 350470#report group size
group_size <- c(nrow(ctwas_gene_res), n_snps)
print(group_size)[1] 11095 8696600#estimated group PVE
estimated_group_pve <- estimated_group_prior_var*estimated_group_prior*group_size/sample_size #check PVE calculation
names(estimated_group_pve) <- c("gene", "snp")
print(estimated_group_pve) gene snp
0.01349 0.08840 #compare sum(PIP*mu2/sample_size) with above PVE calculation
c(sum(ctwas_gene_res$PVE),sum(ctwas_snp_res$PVE))[1] 0.04734 1.38376Genes with highest PIPs
| Version | Author | Date |
|---|---|---|
| 9b01dad | sq-96 | 2023-02-01 |
genename region_tag susie_pip mu2 PVE z num_eqtl
9507 FES 15_43 1.0000 69.96 1.996e-04 -8.565 3
3646 BAZ2B 2_96 1.0000 86.85 2.478e-04 11.470 2
5673 PSEN2 1_116 1.0000 43.18 1.232e-04 -6.932 3
7481 TAGAP 6_103 0.9999 63.68 1.817e-04 -8.331 2
1640 KIAA0391 14_9 0.9997 47.58 1.357e-04 7.386 2
7070 LAPTM5 1_20 0.9995 70.88 2.021e-04 9.228 3
8131 RNF181 2_54 0.9995 2388.15 6.810e-03 -5.029 1
2611 ALDH2 12_67 0.9989 100.35 2.860e-04 -13.934 3
5966 VLDLR 9_3 0.9988 44.52 1.269e-04 6.949 4
893 ARHGAP15 2_85 0.9986 35.02 9.979e-05 7.184 3
1603 SPTLC2 14_36 0.9985 29.11 8.293e-05 -5.000 2
7222 CXCR1 2_129 0.9978 124.38 3.541e-04 11.321 3
2131 ATP13A1 19_15 0.9976 43.80 1.247e-04 6.372 2
8253 TPST1 7_43 0.9966 40.69 1.157e-04 -6.915 2
5908 CREB5 7_24 0.9966 367.89 1.046e-03 -20.722 1
5665 CNIH4 1_114 0.9954 93.65 2.660e-04 -9.203 2
4571 CD101 1_72 0.9950 39.62 1.125e-04 6.256 3
9672 UBE2F 2_141 0.9915 34.17 9.668e-05 -5.523 3
9863 LAMP1 13_62 0.9912 39.43 1.115e-04 -6.303 1
10100 SELL 1_83 0.9901 25.85 7.302e-05 3.837 3
412 ARAP2 4_30 0.9891 68.79 1.942e-04 -8.413 2
8044 TTC39C 18_12 0.9837 40.20 1.128e-04 5.211 1
1102 SLC25A24 1_67 0.9831 34.05 9.552e-05 5.832 3
1459 SPECC1L 22_6 0.9815 23.81 6.667e-05 5.337 2
9899 KIF18B 17_26 0.9810 26.88 7.525e-05 5.374 1
2312 LIPA 10_57 0.9755 40.48 1.127e-04 6.306 4
5360 NLRC5 16_31 0.9737 43.54 1.210e-04 6.504 2
2818 SLC12A7 5_2 0.9724 39.25 1.089e-04 5.708 4
5767 MED12L 3_93 0.9721 25.67 7.121e-05 -4.689 2
6064 PTPRJ 11_29 0.9710 68.03 1.885e-04 -9.800 2
6686 HIST1H2BD 6_20 0.9654 64.52 1.777e-04 9.575 1
9272 ZFPM1 16_54 0.9623 36.63 1.006e-04 -4.645 1
10454 ELANE 19_2 0.9618 25.17 6.906e-05 -4.762 2
3293 KLF12 13_36 0.9603 39.60 1.085e-04 -6.340 1
9410 DDX60L 4_109 0.9602 21.62 5.923e-05 4.427 5
811 ACAP1 17_6 0.9592 62.97 1.723e-04 7.734 2
3323 NEK6 9_64 0.9571 25.90 7.072e-05 5.717 2
9755 UBOX5 20_5 0.9532 27.74 7.546e-05 -4.863 1
1160 ADD1 4_4 0.9513 33.21 9.014e-05 -7.073 1
2969 SPTBN1 2_36 0.9492 47.30 1.281e-04 6.814 3
3758 ATXN1 6_13 0.9474 65.33 1.766e-04 8.173 1
1273 GLG1 16_40 0.9445 24.70 6.657e-05 4.680 2
8108 TET2 4_69 0.9438 25.10 6.759e-05 -5.355 2
2410 MLX 17_25 0.9435 56.41 1.519e-04 7.856 2
9287 CITED4 1_25 0.9421 27.10 7.285e-05 -4.751 2
736 HDHD5 22_1 0.9368 21.46 5.735e-05 3.481 3
4883 HS6ST1 2_75 0.9349 20.24 5.398e-05 -4.140 1
7272 ATXN7 3_43 0.9331 24.57 6.541e-05 -3.706 3
4385 TBC1D14 4_8 0.9297 29.01 7.697e-05 6.255 1
171 UQCRC1 3_34 0.9295 56.67 1.503e-04 -5.030 1
982 CDC14A 1_61 0.9259 19.56 5.168e-05 3.829 2
4658 OSTF1 9_35 0.9251 20.45 5.399e-05 4.056 3
10114 PAQR9 3_87 0.9249 21.18 5.590e-05 -4.049 2
1408 MYO9B 19_14 0.9038 28.58 7.369e-05 5.238 1
1145 ACHE 7_62 0.9002 37.30 9.582e-05 -3.852 1
323 RABEP1 17_5 0.8978 60.04 1.538e-04 8.715 2
4670 ADAM19 5_93 0.8975 23.14 5.926e-05 4.198 2
2033 TIMM50 19_26 0.8936 38.72 9.873e-05 -6.048 2
6935 CPSF4 7_61 0.8884 52.14 1.322e-04 -7.268 2
380 RAI14 5_23 0.8876 19.25 4.876e-05 3.788 1
9299 CCR8 3_28 0.8855 21.89 5.531e-05 -2.931 1
162 TRAF3IP3 1_106 0.8853 24.59 6.211e-05 4.778 2
1386 ITPR3 6_28 0.8796 37.90 9.511e-05 6.171 5
10088 C19orf35 19_4 0.8770 26.89 6.728e-05 -4.583 3
5598 RORC 1_74 0.8766 20.28 5.073e-05 4.101 1
11526 TNFSF12 17_7 0.8729 40.18 1.001e-04 -3.244 3
208 PPP5C 19_32 0.8726 25.17 6.266e-05 -4.940 2
2053 CCDC9 19_33 0.8697 46.13 1.145e-04 6.833 3
755 JMJD6 17_43 0.8670 24.25 5.999e-05 4.742 1
5834 TNFAIP8 5_72 0.8645 54.30 1.340e-04 7.624 1
1473 SLC25A1 22_3 0.8611 20.59 5.058e-05 -4.055 2
2437 SLC9A3R1 17_42 0.8539 46.97 1.144e-04 -7.630 1
7233 EOMES 3_20 0.8459 55.80 1.347e-04 7.596 1
10656 RCSD1 1_82 0.8384 22.55 5.395e-05 4.395 3
9832 ZFP36L1 14_33 0.8319 57.06 1.354e-04 8.072 2
6143 MTMR12 5_22 0.8301 20.79 4.925e-05 -4.003 1
5668 CDC42BPA 1_116 0.8301 23.45 5.555e-05 5.108 2
253 RALBP1 18_7 0.8261 21.01 4.953e-05 -3.959 4
2813 NPR3 5_22 0.8197 21.28 4.977e-05 4.146 1
8907 LRRC25 19_15 0.8190 27.67 6.465e-05 -4.768 1
11105 MEG3 14_52 0.8119 33.89 7.851e-05 5.342 1
1074 REST 4_41 0.8090 96.14 2.219e-04 9.019 1
574 CA11 19_33 0.8058 31.37 7.212e-05 -5.480 2
9085 GPR4 19_32 0.8057 21.02 4.832e-05 4.252 1
7003 MED11 17_4 0.8049 22.21 5.102e-05 4.984 3GO enrichment analysis for genes with PIP>0.5
#number of genes for gene set enrichment
length(genes)[1] 85Uploading 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 amyloid precursor protein metabolic process (GO:0042982) 3/18
Adjusted.P.value Genes
1 0.04849 ADAM19;ACHE;PSEN2
[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
11 Refractory anaemia with excess blasts 0.05699 1/50 1/9703
29 Cholesterol Ester Storage Disease 0.05699 1/50 1/9703
50 Freckles 0.05699 1/50 1/9703
71 Melanosis 0.05699 1/50 1/9703
72 Chloasma 0.05699 1/50 1/9703
111 Wolman Disease 0.05699 1/50 1/9703
131 Cyclic neutropenia 0.05699 1/50 1/9703
132 Cerebellar Gait Ataxia 0.05699 1/50 1/9703
163 Alcohol-Induced Disorders 0.05699 1/50 1/9703
164 Tall stature 0.05699 1/50 1/9703WebGestalt 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!NULL
sessionInfo()R version 4.1.0 (2021-05-18)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)
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] WebGestaltR_0.4.4 disgenet2r_0.99.2 enrichR_3.1 cowplot_1.1.1
[5] ggplot2_3.4.0 workflowr_1.7.0
loaded via a namespace (and not attached):
[1] httr_1.4.4 sass_0.4.4 vroom_1.6.0 bit64_4.0.5
[5] jsonlite_1.8.4 foreach_1.5.2 bslib_0.4.1 assertthat_0.2.1
[9] getPass_0.2-2 highr_0.9 doRNG_1.8.2 blob_1.2.3
[13] yaml_2.3.6 pillar_1.8.1 RSQLite_2.2.19 lattice_0.20-44
[17] glue_1.6.2 digest_0.6.31 promises_1.2.0.1 colorspace_2.0-3
[21] htmltools_0.5.4 httpuv_1.6.7 Matrix_1.3-3 plyr_1.8.8
[25] pkgconfig_2.0.3 scales_1.2.1 svglite_2.1.0 processx_3.8.0
[29] whisker_0.4.1 later_1.3.0 tzdb_0.3.0 git2r_0.30.1
[33] tibble_3.1.8 generics_0.1.3 farver_2.1.0 ellipsis_0.3.2
[37] cachem_1.0.6 withr_2.5.0 cli_3.4.1 crayon_1.5.2
[41] magrittr_2.0.3 memoise_2.0.1 evaluate_0.19 ps_1.7.2
[45] apcluster_1.4.10 fs_1.5.2 fansi_1.0.3 doParallel_1.0.17
[49] tools_4.1.0 data.table_1.14.6 hms_1.1.2 lifecycle_1.0.3
[53] stringr_1.5.0 munsell_0.5.0 rngtools_1.5.2 callr_3.7.3
[57] compiler_4.1.0 jquerylib_0.1.4 systemfonts_1.0.4 rlang_1.0.6
[61] grid_4.1.0 iterators_1.0.14 rstudioapi_0.14 rjson_0.2.21
[65] igraph_1.3.5 labeling_0.4.2 rmarkdown_2.19 gtable_0.3.1
[69] codetools_0.2-18 DBI_1.1.3 curl_4.3.2 reshape2_1.4.4
[73] R6_2.5.1 knitr_1.41 dplyr_1.0.10 fastmap_1.1.0
[77] bit_4.0.5 utf8_1.2.2 rprojroot_2.0.3 readr_2.1.3
[81] stringi_1.7.8 parallel_4.1.0 Rcpp_1.0.9 vctrs_0.5.1
[85] tidyselect_1.2.0 xfun_0.35