LDL - Expression and Splicing Jointly
Sheng Qian
2022-12-17
Last updated: 2023-02-02
Checks: 5 2
Knit directory: cTWAS_analysis/
This reproducible R Markdown analysis was created with workflowr (version 1.7.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.
The R Markdown file has unstaged changes. To know which version of the R Markdown file created these results, you’ll want to first commit it to the Git repo. If you’re still working on the analysis, you can ignore this warning. When you’re finished, you can run wflow_publish to commit the R Markdown file and build the HTML.
Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.
The command set.seed(20211220) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.
Great job! Recording the operating system, R version, and package versions is critical for reproducibility.
Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.
Using absolute paths to the files within your workflowr project makes it difficult for you and others to run your code on a different machine. Change the absolute path(s) below to the suggested relative path(s) to make your code more reproducible.
| absolute | relative |
|---|---|
| /project2/xinhe/shengqian/cTWAS/cTWAS_analysis/data/ | data |
| /project2/xinhe/shengqian/cTWAS/cTWAS_analysis/code/ctwas_config_b38.R | code/ctwas_config_b38.R |
| /project2/xinhe/shengqian/cTWAS/cTWAS_analysis/data/mashr_sqtl/sqtl/mashr/mashr_Liver_Splicing_mapping.RData | data/mashr_sqtl/sqtl/mashr/mashr_Liver_Splicing_mapping.RData |
| /project2/xinhe/shengqian/cTWAS/cTWAS_analysis/data/mashr_sqtl/sqtl/mashr/mashr_Whole_Blood_Splicing_mapping.RData | data/mashr_sqtl/sqtl/mashr/mashr_Whole_Blood_Splicing_mapping.RData |
| /project2/xinhe/shengqian/cTWAS/cTWAS_analysis/data/mqtl/WholeBlood.db | data/mqtl/WholeBlood.db |
Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.
The results in this page were generated with repository version 9b01dad. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.
Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
Ignored files:
Ignored: .Rhistory
Ignored: .ipynb_checkpoints/
Ignored: analysis/figure/
Untracked files:
Untracked: Proposal plots.R
Untracked: RGS14.pdf
Untracked: RNF186.pdf
Untracked: SCZ_annotation.xlsx
Untracked: SLC8B1.pdf
Untracked: analysis/.ipynb_checkpoints/
Untracked: cache/
Untracked: code/.ipynb_checkpoints/
Untracked: data/.ipynb_checkpoints/
Untracked: data/FUMA_output/
Untracked: data/GO_Terms/
Untracked: data/GTEx_Analysis_v8_eQTL.tar
Untracked: data/G_list.RData
Untracked: data/IBD_ME/
Untracked: data/LDL/
Untracked: data/LDL_E_S/
Untracked: data/LDL_M/
Untracked: data/LDL_S/
Untracked: data/LDL_multi/
Untracked: data/PGC3_SCZ_wave3_public.v2.tsv
Untracked: data/RedBlood_M/
Untracked: data/SCZ/
Untracked: data/SCZ_2014_EUR/
Untracked: data/SCZ_2014_EUR_ME/
Untracked: data/SCZ_2018/
Untracked: data/SCZ_2018_ME/
Untracked: data/SCZ_2018_S/
Untracked: data/SCZ_2020/
Untracked: data/SCZ_S/
Untracked: data/Supplementary Table 15 - MAGMA.xlsx
Untracked: data/Supplementary Table 20 - Prioritised Genes.xlsx
Untracked: data/UKBB/
Untracked: data/UKBB_SNPs_Info.text
Untracked: data/WhiteBlood_E_S_M/
Untracked: data/White_Blood_M/
Untracked: data/eqtl/
Untracked: data/gencode.v26.GRCh38.genes.gtf
Untracked: data/gene_OMIM.txt
Untracked: data/gene_pip_0.8.txt
Untracked: data/gwas_sumstats/
Untracked: data/magma.genes.out
Untracked: data/mashr_Heart_Atrial_Appendage.db
Untracked: data/mashr_sqtl/
Untracked: data/mqtl/
Untracked: data/multigroup/
Untracked: data/notes.txt
Untracked: data/scz_2018.RDS
Untracked: data/summary_known_genes_annotations.xlsx
Untracked: temp_LDR/
Untracked: top_genes_32.txt
Untracked: top_genes_37.txt
Untracked: top_genes_43.txt
Untracked: top_genes_54.txt
Untracked: top_genes_81.txt
Untracked: z_snp_pos_SCZ.RData
Untracked: z_snp_pos_SCZ_2014_EUR.RData
Untracked: z_snp_pos_SCZ_2018.RData
Untracked: z_snp_pos_SCZ_2020.RData
Unstaged changes:
Deleted: analysis/Atrial_Fibrillation_Heart_Atrial_Appendage.Rmd
Deleted: analysis/Atrial_Fibrillation_Heart_Left_Ventricle.Rmd
Deleted: analysis/Autism_Brain_Amygdala.Rmd
Deleted: analysis/Autism_Brain_Anterior_cingulate_cortex_BA24.Rmd
Deleted: analysis/Autism_Brain_Caudate_basal_ganglia.Rmd
Deleted: analysis/Autism_Brain_Cerebellar_Hemisphere.Rmd
Deleted: analysis/Autism_Brain_Cerebellum.Rmd
Deleted: analysis/Autism_Brain_Cortex.Rmd
Deleted: analysis/Autism_Brain_Frontal_Cortex_BA9.Rmd
Deleted: analysis/Autism_Brain_Hippocampus.Rmd
Deleted: analysis/Autism_Brain_Hypothalamus.Rmd
Deleted: analysis/Autism_Brain_Nucleus_accumbens_basal_ganglia.Rmd
Deleted: analysis/Autism_Brain_Putamen_basal_ganglia.Rmd
Deleted: analysis/Autism_Brain_Spinal_cord_cervical_c-1.Rmd
Deleted: analysis/Autism_Brain_Substantia_nigra.Rmd
Deleted: analysis/BMI_Brain_Amygdala.Rmd
Deleted: analysis/BMI_Brain_Amygdala_S.Rmd
Deleted: analysis/BMI_Brain_Anterior_cingulate_cortex_BA24.Rmd
Deleted: analysis/BMI_Brain_Anterior_cingulate_cortex_BA24_S.Rmd
Deleted: analysis/BMI_Brain_Caudate_basal_ganglia.Rmd
Deleted: analysis/BMI_Brain_Caudate_basal_ganglia_S.Rmd
Deleted: analysis/BMI_Brain_Cerebellar_Hemisphere.Rmd
Deleted: analysis/BMI_Brain_Cerebellar_Hemisphere_S.Rmd
Deleted: analysis/BMI_Brain_Cerebellum.Rmd
Deleted: analysis/BMI_Brain_Cerebellum_S.Rmd
Deleted: analysis/BMI_Brain_Cortex.Rmd
Deleted: analysis/BMI_Brain_Cortex_S.Rmd
Deleted: analysis/BMI_Brain_Frontal_Cortex_BA9.Rmd
Deleted: analysis/BMI_Brain_Frontal_Cortex_BA9_S.Rmd
Deleted: analysis/BMI_Brain_Hippocampus.Rmd
Deleted: analysis/BMI_Brain_Hippocampus_S.Rmd
Deleted: analysis/BMI_Brain_Hypothalamus.Rmd
Deleted: analysis/BMI_Brain_Hypothalamus_S.Rmd
Deleted: analysis/BMI_Brain_Nucleus_accumbens_basal_ganglia.Rmd
Deleted: analysis/BMI_Brain_Nucleus_accumbens_basal_ganglia_S.Rmd
Deleted: analysis/BMI_Brain_Putamen_basal_ganglia.Rmd
Deleted: analysis/BMI_Brain_Putamen_basal_ganglia_S.Rmd
Deleted: analysis/BMI_Brain_Spinal_cord_cervical_c-1.Rmd
Deleted: analysis/BMI_Brain_Spinal_cord_cervical_c-1_S.Rmd
Deleted: analysis/BMI_Brain_Substantia_nigra.Rmd
Deleted: analysis/BMI_Brain_Substantia_nigra_S.Rmd
Deleted: analysis/BMI_S_results.Rmd
Deleted: analysis/Glucose_Adipose_Subcutaneous.Rmd
Deleted: analysis/Glucose_Adipose_Visceral_Omentum.Rmd
Modified: analysis/LDL_Liver_E_S.Rmd
Modified: analysis/WhiteBlood_WholeBlood_E_S_M.Rmd
Modified: analysis/index.Rmd
Deleted: code/run_IBD_ctwas_rss_LDR_ME.R
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the repository in which changes were made to the R Markdown (analysis/WhiteBlood_WholeBlood_E_S_M.Rmd) and HTML (docs/WhiteBlood_WholeBlood_E_S_M.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 9b01dad | sq-96 | 2023-02-01 | update |
analysis_id <- params$analysis_id
trait_id <- params$trait_id
weight <- params$weight
results_dir <- paste0("/project2/xinhe/shengqian/cTWAS/cTWAS_analysis/data/", trait_id, "/", weight)
source("/project2/xinhe/shengqian/cTWAS/cTWAS_analysis/code/ctwas_config_b38.R")
options(digits = 4)Load ctwas results
Check convergence of parameters
#estimated group prior
estimated_group_prior <- estimated_group_prior_all[,ncol(group_prior_rec)]
print(estimated_group_prior) SNP Whole_Blood Whole_Blood_Splicing
0.0001751 0.0225055 0.0052580
Whole_Blood_Methylation
0.0108737 #estimated group prior variance
estimated_group_prior_var <- estimated_group_prior_var_all[,ncol(group_prior_var_rec)]
print(estimated_group_prior_var) SNP Whole_Blood Whole_Blood_Splicing
15.55 19.40 29.53
Whole_Blood_Methylation
14.35 #estimated enrichment
estimated_enrichment <- estimated_enrichment_all[ncol(group_prior_var_rec)]
print(estimated_enrichment)[1] 61.79#report sample size
print(sample_size)[1] 350470#report group size
print(group_size) SNP Whole_Blood Whole_Blood_Splicing
8696600 11198 20134
Whole_Blood_Methylation
11858 #estimated group PVE
estimated_group_pve <- estimated_group_pve_all[,ncol(group_prior_rec)]
print(estimated_group_pve) SNP Whole_Blood Whole_Blood_Splicing
0.067547 0.013950 0.008919
Whole_Blood_Methylation
0.005278 #total PVE
sum(estimated_group_pve)[1] 0.09569#attributable PVE
estimated_group_pve/sum(estimated_group_pve) SNP Whole_Blood Whole_Blood_Splicing
0.70586 0.14578 0.09320
Whole_Blood_Methylation
0.05515 #load information for all genes
sqlite <- RSQLite::dbDriver("SQLite")
db = RSQLite::dbConnect(sqlite, "/project2/compbio/predictdb/mashr_models/mashr_Whole_Blood.db")
query <- function(...) RSQLite::dbGetQuery(db, ...)
gene_info <- query("select gene, genename from extra")
RSQLite::dbDisconnect(db)
ctwas_gene_E_res$genename <- gene_info[sapply(ctwas_gene_E_res$gene_id, match, gene_info$gene),"genename"]
load("/project2/xinhe/shengqian/cTWAS/cTWAS_analysis/data/mashr_sqtl/sqtl/mashr/mashr_Whole_Blood_Splicing_mapping.RData")
ctwas_gene_S_res$genename <- intron_info[sapply(ctwas_gene_S_res$gene_id, match, intron_info$gene), "genename"]
sqlite <- RSQLite::dbDriver("SQLite")
db = RSQLite::dbConnect(sqlite, "/project2/xinhe/shengqian/cTWAS/cTWAS_analysis/data/mqtl/WholeBlood.db")
query <- function(...) RSQLite::dbGetQuery(db, ...)
gene_info <- query("select gene, genename from extra")
RSQLite::dbDisconnect(db)
ctwas_gene_M_res$genename <- gene_info[sapply(ctwas_gene_M_res$gene_id, match, gene_info$gene),"genename"]
ctwas_gene_M_res$genename <- sapply(ctwas_gene_M_res$genename, function(x){unlist(strsplit(x, split="[;]"))[1]})Top expression/intron/CpG
genename gene_id group region_tag
39936 FES ENSG00000182511.11 Expression 15_43
43125 YBEY intron_21_46287123_46296162 Splicing 21_24
38047 TAGAP ENSG00000164691.16 Expression 6_103
36651 ARHGAP15 ENSG00000075884.13 Expression 2_85
41903 CNN2 intron_19_1032696_1036130 Splicing 19_2
36665 BAZ2B ENSG00000123636.17 Expression 2_96
38535 VLDLR ENSG00000147852.15 Expression 9_3
39701 KIAA0391 ENSG00000100890.15 Expression 14_9
38156 CREB5 ENSG00000146592.16 Expression 7_24
37171 MED12L ENSG00000144893.12 Expression 3_93
35946 LAPTM5 ENSG00000162511.7 Expression 1_20
37527 SLC22A4 ENSG00000197208.5 Expression 5_79
37106 ATXN7 ENSG00000163635.17 Expression 3_43
39549 FLT3 intron_13_28024943_28027088 Splicing 13_7
36279 CNIH4 ENSG00000143771.11 Expression 1_114
39447 ALDH2 ENSG00000111275.12 Expression 12_67
39604 LAMP1 ENSG00000185896.10 Expression 13_62
36089 SLC25A24 ENSG00000085491.15 Expression 1_67
43166 HDHD5 ENSG00000069998.12 Expression 22_1
41827 TTC39C ENSG00000168234.12 Expression 18_12
41159 YPEL2 ENSG00000175155.8 Expression 17_34
38704 LIPA ENSG00000107798.17 Expression 10_57
41100 KIF18B ENSG00000186185.13 Expression 17_26
39339 ACVRL1 cg21236262 Methylation 12_33
38973 PTPRJ ENSG00000149177.12 Expression 11_29
37291 ARAP2 ENSG00000047365.11 Expression 4_30
37629 CPEB4 ENSG00000113742.12 Expression 5_104
40700 MYO1C cg02622416 Methylation 17_2
40445 ZFPM1 ENSG00000179588.8 Expression 16_54
38575 OSTF1 ENSG00000134996.11 Expression 9_35
39588 KLF12 ENSG00000118922.17 Expression 13_36
36440 ITSN2 intron_2_24209221_24209818 Splicing 2_14
37693 ATXN1 ENSG00000124788.17 Expression 6_13
38633 NEK6 ENSG00000119408.16 Expression 9_64
36934 UQCRC1 ENSG00000010256.10 Expression 3_34
40367 GLG1 ENSG00000090863.11 Expression 16_40
37233 ADD1 ENSG00000087274.16 Expression 4_4
37348 TET2 ENSG00000168769.13 Expression 4_69
36222 SELL ENSG00000188404.8 Expression 1_83
36005 CITED4 ENSG00000179862.6 Expression 1_25
37276 TBC1D14 ENSG00000132405.18 Expression 4_8
37664 CANX intron_5_179699102_179705679 Splicing 5_108
36622 HS6ST1 ENSG00000136720.6 Expression 2_75
36670 CD302 ENSG00000241399.6 Expression 2_96
39154 CD6 cg27098804 Methylation 11_34
36067 CDC14A ENSG00000079335.18 Expression 1_61
37398 DDX60L ENSG00000181381.13 Expression 4_109
42503 ATP13A1 ENSG00000105726.16 Expression 19_15
42083 CTC-503J8.4 cg14319541 Methylation 19_6
42362 MYO9B ENSG00000099331.13 Expression 19_14
40361 ITGAL cg24033122 Methylation 16_24
42233 AP1M2 ENSG00000129354.11 Expression 19_9
39185 AP000908.1 cg04049253 Methylation 11_67
36881 CCR8 ENSG00000179934.6 Expression 3_28
37134 PAQR9 ENSG00000188582.8 Expression 3_87
37511 TNFAIP8 ENSG00000145779.7 Expression 5_72
37102 CTD-2330K9.3 cg24308560 Methylation 3_35
37439 RAI14 ENSG00000039560.13 Expression 5_23
38269 CPSF4 ENSG00000160917.14 Expression 7_61
37608 ADAM19 ENSG00000135074.15 Expression 5_93
38449 RNF139-AS1 ENSG00000245149.3 Expression 8_82
36265 NCF2 intron_1_183570839_183573185 Splicing 1_91
41207 SLC9A3R1 ENSG00000109062.11 Expression 17_42
38476 RP11-136O12.2 cg09660151 Methylation 8_83
37185 ABCC5 ENSG00000114770.16 Expression 3_112
41423 UBE2O ENSG00000175931.12 Expression 17_43
37312 REST ENSG00000084093.16 Expression 4_41
39271 CERS5 intron_12_50134068_50134546 Splicing 12_33
42844 UBOX5 ENSG00000185019.16 Expression 20_5
36462 DTNB ENSG00000138101.18 Expression 2_15
37475 ZBED3 ENSG00000132846.5 Expression 5_45
39884 MEG3 ENSG00000214548.14 Expression 14_52
38383 ACHE ENSG00000087085.13 Expression 7_62
38011 L3MBTL3 ENSG00000198945.7 Expression 6_86
37418 NPR3 ENSG00000113389.15 Expression 5_22
37369 LRBA intron_4_150278004_150282450 Splicing 4_98
37420 MTMR12 ENSG00000150712.10 Expression 5_22
36185 RCSD1 ENSG00000198771.10 Expression 1_82
41409 JMJD6 ENSG00000070495.14 Expression 17_43
37118 PXYLP1 ENSG00000155893.12 Expression 3_86
39582 KLF5 ENSG00000102554.13 Expression 13_35
41886 ELANE ENSG00000197561.6 Expression 19_2
38127 JAZF1 ENSG00000153814.11 Expression 7_23
37994 HSF2 ENSG00000025156.12 Expression 6_82
39810 ZFP36L1 ENSG00000185650.9 Expression 14_33
42600 LSM4 cg15796753 Methylation 19_15
38758 RBP4 ENSG00000138207.13 Expression 10_59
susie_pip mu2 PVE z
39936 1.0000 74.88 2.136e-04 -8.8371
43125 1.0000 21567.58 6.154e-02 -4.5377
38047 1.0000 71.28 2.034e-04 -8.4352
36651 1.0000 51.50 1.469e-04 9.1934
41903 1.0000 69.78 1.991e-04 -8.4588
36665 0.9999 73.32 2.092e-04 11.1020
38535 0.9999 54.10 1.544e-04 7.8169
39701 0.9997 47.53 1.356e-04 7.3702
38156 0.9991 368.21 1.050e-03 -20.7223
37171 0.9981 32.91 9.372e-05 -5.4270
35946 0.9981 68.29 1.945e-04 9.1174
37527 0.9966 142.46 4.051e-04 13.7538
37106 0.9965 47.41 1.348e-04 -3.6298
39549 0.9949 263.79 7.488e-04 -14.2245
36279 0.9948 101.68 2.886e-04 -9.4218
39447 0.9941 139.67 3.962e-04 -15.8148
39604 0.9931 39.66 1.124e-04 -6.3026
36089 0.9924 35.34 1.001e-04 5.9415
43166 0.9912 25.37 7.175e-05 4.1322
41827 0.9872 40.10 1.130e-04 5.2107
41159 0.9846 31.57 8.868e-05 -0.2668
38704 0.9839 41.70 1.171e-04 6.3863
41100 0.9837 27.95 7.845e-05 5.3743
39339 0.9824 51.79 1.452e-04 -7.2809
38973 0.9824 66.16 1.854e-04 -9.8176
37291 0.9783 66.58 1.858e-04 -8.2624
37629 0.9741 123.48 3.432e-04 12.4516
40700 0.9736 42.91 1.192e-04 6.5882
40445 0.9711 36.75 1.018e-04 -4.6448
38575 0.9691 21.77 6.019e-05 4.2476
39588 0.9685 39.60 1.094e-04 -6.3398
36440 0.9663 68.78 1.896e-04 10.5178
37693 0.9616 65.29 1.791e-04 8.1734
38633 0.9567 25.84 7.053e-05 5.7063
36934 0.9555 32.60 8.887e-05 -5.0296
40367 0.9553 25.07 6.834e-05 4.6834
37233 0.9550 32.38 8.824e-05 -7.0727
37348 0.9535 25.07 6.820e-05 -5.2844
36222 0.9505 22.81 6.187e-05 3.9041
36005 0.9505 27.05 7.336e-05 -4.7501
37276 0.9442 28.72 7.736e-05 6.2554
37664 0.9434 53.46 1.439e-04 -7.3165
36622 0.9385 20.34 5.447e-05 -4.1404
36670 0.9303 33.09 8.784e-05 -6.7895
39154 0.9266 24.32 6.430e-05 -4.2787
36067 0.9259 19.54 5.161e-05 3.8255
37398 0.9238 21.38 5.636e-05 4.4610
42503 0.9228 41.60 1.095e-04 6.1665
42083 0.9227 22.20 5.846e-05 -4.4401
42362 0.9165 28.36 7.417e-05 5.2380
40361 0.9158 146.78 3.835e-04 12.4780
42233 0.9144 38.67 1.009e-04 5.0990
39185 0.9088 73.48 1.905e-04 -8.0026
36881 0.9073 22.07 5.714e-05 -2.9305
37134 0.9002 21.29 5.469e-05 -4.0819
37511 0.8984 53.56 1.373e-04 7.6239
37102 0.8970 65.68 1.681e-04 -8.4136
37439 0.8925 19.19 4.888e-05 3.7885
38269 0.8870 51.39 1.301e-04 -7.2534
37608 0.8862 22.67 5.732e-05 4.0890
38449 0.8838 22.66 5.715e-05 4.4502
36265 0.8821 25.49 6.414e-05 4.3322
41207 0.8776 46.73 1.170e-04 -7.6296
38476 0.8753 34.29 8.564e-05 5.7186
37185 0.8707 44.34 1.102e-04 -6.2110
41423 0.8706 27.61 6.857e-05 -5.5016
37312 0.8678 95.68 2.369e-04 9.0191
39271 0.8677 100.30 2.483e-04 -9.9457
42844 0.8644 26.29 6.485e-05 -4.8630
36462 0.8556 22.68 5.536e-05 -4.5901
37475 0.8554 19.97 4.875e-05 3.8017
39884 0.8479 34.36 8.312e-05 5.3419
38383 0.8461 36.23 8.747e-05 -3.8520
38011 0.8426 31.08 7.471e-05 -5.5795
37418 0.8420 21.27 5.110e-05 4.1456
37369 0.8388 30.88 7.391e-05 -5.2425
37420 0.8381 20.71 4.952e-05 -4.0032
36185 0.8329 22.22 5.280e-05 4.3451
41409 0.8306 25.19 5.970e-05 4.7425
37118 0.8284 31.77 7.510e-05 7.2189
39582 0.8242 23.36 5.493e-05 -4.5126
41886 0.8125 26.42 6.125e-05 -4.5516
38127 0.8109 122.01 2.823e-04 -14.6257
37994 0.8108 66.37 1.535e-04 8.2271
39810 0.8106 56.09 1.297e-04 8.0724
42600 0.8058 23.37 5.373e-05 3.8635
38758 0.8035 22.80 5.227e-05 4.4358Top genes by expression/splicing/methylation
ctwas_gene_E_res <- ctwas_gene_res[ctwas_gene_res$group=="Expression",]
ctwas_gene_S_res <- ctwas_gene_res[ctwas_gene_res$group=="Splicing",]
ctwas_gene_M_res <- ctwas_gene_res[ctwas_gene_res$group=="Methylation",]
df_gene_E <- aggregate(ctwas_gene_E_res$susie_pip,by=list(ctwas_gene_E_res$genename), FUN=sum)
colnames(df_gene_E) <- c("genename", "susie_pip")
df_gene_E$group <- "Expression"
df_gene_S <- aggregate(ctwas_gene_S_res$susie_pip,by=list(ctwas_gene_S_res$genename), FUN=sum)
colnames(df_gene_S) <- c("genename", "susie_pip")
df_gene_S$group <- "Splicing"
df_gene_M <- aggregate(ctwas_gene_M_res$susie_pip,by=list(ctwas_gene_M_res$genename), FUN=sum)
colnames(df_gene_M) <- c("genename", "susie_pip")
df_gene_M$group <- "Methylation"
df_gene <- rbind(df_gene_E,df_gene_S,df_gene_M)
head(df_gene[order(-df_gene$susie_pip),], max(sum(df_gene$susie_pip>0.8), 20)) genename susie_pip group
14585 MYO1G 1.3514 Splicing
21011 NINJ2 1.1701 Methylation
17145 TSPAN32 1.1599 Splicing
18178 AMZ1 1.0639 Methylation
13814 ITSN2 1.0254 Splicing
16153 SIRPB1 1.0210 Splicing
21542 PTPRN2 1.0060 Methylation
14179 LYZ 1.0001 Splicing
12347 CNN2 1.0000 Splicing
3340 FES 1.0000 Expression
17524 YBEY 1.0000 Splicing
9381 TAGAP 1.0000 Expression
612 ARHGAP15 1.0000 Expression
906 BAZ2B 0.9999 Expression
10464 VLDLR 0.9999 Expression
4601 KIAA0391 0.9997 Expression
15547 RAB34 0.9995 Splicing
2141 CREB5 0.9991 Expression
19483 ELK3 0.9989 Methylation
5430 MED12L 0.9981 Expression
4787 LAPTM5 0.9981 Expression
15509 PVT1 0.9970 Splicing
8729 SLC22A4 0.9966 Expression
842 ATXN7 0.9965 Expression
13190 FLT3 0.9955 Splicing
1966 CNIH4 0.9948 Expression
379 ALDH2 0.9941 Expression
11991 CANX 0.9939 Splicing
4777 LAMP1 0.9931 Expression
8746 SLC25A24 0.9924 Expression
3989 HDHD5 0.9912 Expression
22612 SPTLC2 0.9895 Methylation
10159 TTC39C 0.9872 Expression
10660 YPEL2 0.9846 Expression
5067 LIPA 0.9839 Expression
4637 KIF18B 0.9837 Expression
18048 ACVRL1 0.9824 Methylation
7334 PTPRJ 0.9824 Expression
16974 TNFRSF1A 0.9794 Splicing
593 ARAP2 0.9783 Expression
2102 CPEB4 0.9741 Expression
20919 MYO1C 0.9736 Methylation
10770 ZFPM1 0.9711 Expression
22247 RRBP1 0.9698 Methylation
6450 OSTF1 0.9691 Expression
4669 KLF12 0.9685 Expression
836 ATXN1 0.9616 Expression
6067 NEK6 0.9567 Expression
10365 UQCRC1 0.9555 Expression
3654 GLG1 0.9553 Expression
236 ADD1 0.9550 Expression
9518 TET2 0.9535 Expression
22284 SBNO2 0.9509 Methylation
8491 SELL 0.9505 Expression
1860 CITED4 0.9505 Expression
20541 LINC01344 0.9445 Methylation
9417 TBC1D14 0.9442 Expression
14644 NCF2 0.9422 Splicing
4174 HS6ST1 0.9385 Expression
16859 TMCC2 0.9337 Splicing
1581 CD302 0.9303 Expression
18771 CD6 0.9266 Methylation
1618 CDC14A 0.9259 Expression
2499 DDX60L 0.9238 Expression
784 ATP13A1 0.9228 Expression
19114 CTC-503J8.4 0.9227 Methylation
5891 MYO9B 0.9165 Expression
20201 ITGAL 0.9161 Methylation
526 AP1M2 0.9144 Expression
18232 AP000908.1 0.9088 Methylation
1540 CCR8 0.9073 Expression
14342 MFSD13A 0.9073 Splicing
15435 PSD4 0.9016 Splicing
6532 PAQR9 0.9002 Expression
9851 TNFAIP8 0.8984 Expression
19159 CTD-2330K9.3 0.8970 Methylation
23167 ZBTB2 0.8967 Methylation
7466 RAI14 0.8925 Expression
2118 CPSF4 0.8870 Expression
209 ADAM19 0.8862 Expression
17450 WDFY2 0.8849 Splicing
7727 RNF139-AS1 0.8838 Expression
8873 SLC9A3R1 0.8776 Expression
21805 RP11-136O12.2 0.8753 Methylation
38 ABCC5 0.8707 Expression
10268 UBE2O 0.8706 Expression
7605 REST 0.8678 Expression
12228 CERS5 0.8677 Splicing
10288 UBOX5 0.8644 Expression
15191 PLCB2 0.8623 Splicing
19656 FBRSL1 0.8596 Methylation
2724 DTNB 0.8556 Expression
10678 ZBED3 0.8554 Expression
5455 MEG3 0.8479 Expression
145 ACHE 0.8461 Expression
4760 L3MBTL3 0.8426 Expression
6227 NPR3 0.8420 Expression
23028 UBE2I 0.8420 Methylation
14111 LRBA 0.8388 Splicing
5805 MTMR12 0.8381 Expression
7579 RCSD1 0.8329 Expression
4502 JMJD6 0.8306 Expression
7364 PXYLP1 0.8284 Expression
4673 KLF5 0.8242 Expression
12044 CCDC125 0.8207 Splicing
19896 GPR126 0.8181 Methylation
2884 ELANE 0.8125 Expression
4499 JAZF1 0.8109 Expression
4191 HSF2 0.8108 Expression
10760 ZFP36L1 0.8106 Expression
20619 LSM4 0.8058 Methylation
18274 APOLD1 0.8042 Methylation
7557 RBP4 0.8035 ExpressionTop genes by combined PIP
genename combined_pip expression_pip splicing_pip methylation_pip
14632 YPEL2 1.7531 0.985 0.000 0.768
6635 LAPTM5 1.7444 0.998 0.002 0.744
1036 ARHGAP15 1.7228 1.000 0.680 0.042
8086 MYO1G 1.4333 0.082 1.351 0.000
12304 SLC45A4 1.3131 0.786 0.509 0.018
3603 DDX60L 1.2453 0.924 0.322 0.000
13604 TNFAIP8 1.2375 0.898 0.120 0.219
5556 HDHD5 1.2168 0.991 0.226 0.000
8382 NINJ2 1.2094 0.033 0.006 1.170
7276 LYZ 1.1825 0.182 1.000 0.000
12684 SPTLC2 1.1762 0.187 0.000 0.989
13938 TSPAN32 1.1634 0.004 1.160 0.000
11576 RRBP1 1.1285 0.066 0.093 0.970
12119 SLC12A7 1.0927 0.416 0.011 0.666
1319 ATXN1 1.0859 0.962 0.058 0.067
383 ACAP1 1.0827 0.349 0.015 0.719
6369 KIAA0391 1.0714 1.000 0.072 0.000
6195 ITSN2 1.0710 0.033 1.025 0.013
773 AMZ1 1.0639 0.000 0.000 1.064
12080 SIRPB1 1.0583 0.037 1.021 0.000
6108 IQGAP2 1.0558 0.443 0.589 0.024
518 ADD1 1.0546 0.955 0.100 0.000
9680 PPP5C 1.0500 0.436 0.004 0.610
14724 ZDHHC18 1.0485 0.009 0.590 0.450
8411 NLRC5 1.0472 0.676 0.074 0.297
4214 EOMES 1.0430 0.645 0.009 0.389
4131 ELK3 1.0411 0.031 0.012 0.999
1325 ATXN7 1.0395 0.997 0.043 0.000
4614 FBRSL1 1.0389 0.063 0.117 0.860
13618 TNFRSF1A 1.0375 0.016 0.979 0.042
9965 PTPRJ 1.0347 0.982 0.015 0.038
13069 TBC1D14 1.0311 0.944 0.062 0.025
2270 CD101 1.0281 0.702 0.006 0.320
2797 CNIH4 1.0177 0.995 0.023 0.000
7508 MED12L 1.0147 0.998 0.000 0.017
700 ALDH2 1.0137 0.994 0.020 0.000
4709 FES 1.0119 1.000 0.012 0.000
6467 KLF12 1.0068 0.968 0.038 0.000
9969 PTPRN2 1.0060 0.000 0.000 1.006
4281 ERICH1 1.0036 0.046 0.203 0.754
14370 VLDLR 1.0036 1.000 0.004 0.000
3021 CREB5 1.0014 0.999 0.002 0.000
5641 HIST1H2BD 1.0009 0.675 0.326 0.000
13024 TAGAP 1.0007 1.000 0.001 0.000
10073 RAB34 1.0006 0.001 1.000 0.000
1413 BAZ2B 1.0005 1.000 0.001 0.000
2800 CNN2 1.0001 0.000 1.000 0.000
14611 YBEY 1.0000 0.000 1.000 0.000
8082 MYO1C 0.9998 0.026 0.000 0.974
2973 CPEB4 0.9996 0.974 0.000 0.025
1010 ARAP2 0.9992 0.978 0.021 0.000
12164 SLC22A4 0.9982 0.997 0.002 0.000
9992 PVT1 0.9970 0.000 0.997 0.000
12185 SLC25A24 0.9967 0.992 0.004 0.000
4794 FLT3 0.9955 0.000 0.995 0.000
1989 CANX 0.9939 0.000 0.994 0.000
6622 LAMP1 0.9931 0.993 0.000 0.000
8827 OSTF1 0.9924 0.969 0.023 0.000
10577 RORC 0.9913 0.776 0.000 0.216
7047 LIPA 0.9908 0.984 0.006 0.001
2305 CD33 0.9902 0.039 0.767 0.184
13990 TTC39C 0.9878 0.987 0.001 0.000
9368 PLCB2 0.9837 0.121 0.862 0.000
6422 KIF18B 0.9837 0.984 0.000 0.000
461 ACVRL1 0.9824 0.000 0.000 0.982
13753 TRAF3IP3 0.9776 0.686 0.292 0.000
13372 TMCC2 0.9776 0.044 0.934 0.000
14766 ZFPM1 0.9726 0.971 0.001 0.000
14122 UBE2I 0.9675 0.067 0.059 0.842
8311 NEK6 0.9663 0.957 0.004 0.006
8667 NUP88 0.9649 0.172 0.767 0.026
3917 DTNB 0.9621 0.856 0.005 0.102
5125 GLG1 0.9580 0.955 0.003 0.000
12320 SLC5A11 0.9579 0.302 0.000 0.656
14154 UBOX5 0.9568 0.864 0.092 0.000
13190 TET2 0.9561 0.953 0.003 0.000
14245 UQCRC1 0.9555 0.956 0.000 0.000
11857 SELL 0.9551 0.951 0.005 0.000
5796 HS6ST1 0.9546 0.939 0.000 0.016
11724 SBNO2 0.9517 0.000 0.001 0.951
2665 CITED4 0.9505 0.951 0.000 0.000
7741 MLX 0.9491 0.735 0.214 0.000
6957 LINC01344 0.9445 0.000 0.000 0.944
8211 NCF2 0.9422 0.000 0.942 0.000
14663 ZBTB2 0.9364 0.040 0.000 0.897
5386 GSAP 0.9319 0.630 0.262 0.040
2303 CD302 0.9303 0.930 0.000 0.000
2324 CD6 0.9275 0.000 0.001 0.927
2345 CDC14A 0.9259 0.926 0.000 0.000
1244 ATP13A1 0.9248 0.923 0.002 0.000
3188 CTC-503J8.4 0.9227 0.000 0.000 0.923
1782 C20orf96 0.9196 0.721 0.060 0.138
14462 WDFY2 0.9185 0.000 0.885 0.034
54 ABCC5 0.9167 0.871 0.019 0.027
8095 MYO9B 0.9166 0.917 0.000 0.000
6163 ITGAL 0.9161 0.000 0.000 0.916
928 AP1M2 0.9144 0.914 0.000 0.000
6360 KIAA0040 0.9139 0.067 0.085 0.762
10132 RAI14 0.9131 0.892 0.000 0.021
897 AP000908.1 0.9088 0.000 0.000 0.909
2253 CCR8 0.9073 0.907 0.000 0.000
7609 MFSD13A 0.9073 0.000 0.907 0.000
7989 MTMR12 0.9019 0.838 0.064 0.000
9846 PSD4 0.9016 0.000 0.902 0.000
8937 PAQR9 0.9002 0.900 0.000 0.000
472 ADAM19 0.8995 0.886 0.005 0.008
3263 CTD-2330K9.3 0.8970 0.000 0.000 0.897
11679 SAE1 0.8945 0.622 0.272 0.000
2992 CPSF4 0.8870 0.887 0.000 0.000
10482 RNF139-AS1 0.8838 0.884 0.000 0.000
7346 MAP2K5 0.8800 0.070 0.030 0.780
12350 SLC9A3R1 0.8776 0.878 0.000 0.000
2306 CD36 0.8767 0.563 0.314 0.000
10674 RP11-136O12.2 0.8753 0.000 0.000 0.875
6217 JAZF1 0.8744 0.811 0.063 0.000
7158 LRRC25 0.8725 0.735 0.137 0.000
14129 UBE2O 0.8711 0.871 0.001 0.000
8626 NUDT14 0.8711 0.216 0.557 0.098
6596 L3MBTL3 0.8697 0.843 0.000 0.027
2526 CERS5 0.8680 0.000 0.868 0.000
10311 REST 0.8678 0.868 0.000 0.000
7125 LRBA 0.8612 0.000 0.839 0.022
2194 CCDC9 0.8583 0.667 0.191 0.000
3811 DNASE1 0.8580 0.551 0.007 0.300
14655 ZBED3 0.8554 0.855 0.000 0.000
2101 CCDC125 0.8550 0.034 0.821 0.000
399 ACHE 0.8510 0.846 0.005 0.000
9934 PTK2B 0.8493 0.739 0.053 0.057
7537 MEG3 0.8479 0.848 0.000 0.000
10281 RCSD1 0.8459 0.833 0.008 0.005
9839 PRUNE2 0.8427 0.799 0.006 0.038
8514 NPR3 0.8420 0.842 0.000 0.000
6222 JMJD6 0.8357 0.831 0.005 0.000
10007 PXYLP1 0.8357 0.828 0.007 0.000
1132 ARRB2 0.8356 0.281 0.554 0.000
4136 ELMO1 0.8347 0.702 0.046 0.086
991 APOLD1 0.8331 0.029 0.000 0.804
6472 KLF5 0.8242 0.824 0.000 0.000
5285 GPR126 0.8181 0.000 0.000 0.818
7213 LSM4 0.8177 0.011 0.001 0.806
2054 CATSPER2 0.8145 0.792 0.000 0.023
4123 ELANE 0.8130 0.813 0.000 0.000
11608 RSU1 0.8115 0.037 0.270 0.505
5816 HSF2 0.8108 0.811 0.000 0.000
14754 ZFP36L1 0.8106 0.811 0.000 0.000
1045 ARHGAP26 0.8096 0.000 0.022 0.788
1065 ARHGEF12 0.8087 0.762 0.046 0.000
7412 MARK3 0.8072 0.696 0.109 0.002
15001 ZNF516 0.8067 0.792 0.004 0.011
468 ADAM10 0.8067 0.798 0.009 0.000
10256 RBP4 0.8035 0.804 0.000 0.000
13327 TLDC1 0.8018 0.079 0.000 0.723GO enrichment analysis for genes with PIP>0.5
#number of genes for gene set enrichment
length(genes)DisGeNET enrichment analysis for genes with PIP>0.5
WebGestalt enrichment analysis for genes with PIP>0.5
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] cowplot_1.1.1 ggplot2_3.4.0 workflowr_1.7.0
loaded via a namespace (and not attached):
[1] tidyselect_1.2.0 xfun_0.35 bslib_0.4.1 colorspace_2.0-3
[5] vctrs_0.5.1 generics_0.1.3 htmltools_0.5.4 yaml_2.3.6
[9] utf8_1.2.2 rlang_1.0.6 jquerylib_0.1.4 later_1.3.0
[13] pillar_1.8.1 glue_1.6.2 withr_2.5.0 DBI_1.1.3
[17] lifecycle_1.0.3 stringr_1.5.0 munsell_0.5.0 gtable_0.3.1
[21] evaluate_0.19 labeling_0.4.2 knitr_1.41 callr_3.7.3
[25] fastmap_1.1.0 httpuv_1.6.7 ps_1.7.2 fansi_1.0.3
[29] highr_0.9 Rcpp_1.0.9 promises_1.2.0.1 scales_1.2.1
[33] cachem_1.0.6 jsonlite_1.8.4 farver_2.1.0 fs_1.5.2
[37] digest_0.6.31 stringi_1.7.8 processx_3.8.0 dplyr_1.0.10
[41] getPass_0.2-2 rprojroot_2.0.3 grid_4.1.0 cli_3.4.1
[45] tools_4.1.0 magrittr_2.0.3 sass_0.4.4 tibble_3.1.8
[49] whisker_0.4.1 pkgconfig_2.0.3 data.table_1.14.6 assertthat_0.2.1
[53] rmarkdown_2.19 httr_1.4.4 rstudioapi_0.14 R6_2.5.1
[57] git2r_0.30.1 compiler_4.1.0