White Blood - Prostate
sheng Qian
2022-10-18
Last updated: 2023-01-26
Checks: 6 1
Knit directory: cTWAS_analysis/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| html | 684d806 | sq-96 | 2023-01-26 | update |
| Rmd | 363ce6a | sq-96 | 2023-01-26 | update |
Weight QC
[1] 48748[1] 43661
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
4104 3452 2299 1938 2229 2922 2432 1993 1233 2189 2583 2100 1147 1395 1414 2130
17 18 19 20 21 22
2453 756 1841 1210 708 1133 [1] 1Load ctwas results
Check convergence of parameters
| Version | Author | Date |
|---|---|---|
| 684d806 | sq-96 | 2023-01-26 |
#estimated group prior
estimated_group_prior <- estimated_group_prior_all[,ncol(group_prior_rec)]
print(estimated_group_prior) SNP gene
0.0002067 0.0076251 #estimated group prior variance
estimated_group_prior_var <- estimated_group_prior_var_all[,ncol(group_prior_var_rec)]
print(estimated_group_prior_var) SNP gene
17.08 25.87 #estimated enrichment
estimated_enrichment <- estimated_enrichment_all[ncol(group_prior_var_rec)]
print(estimated_enrichment)[1] 36.88#report sample size
print(sample_size)[1] 350470#report group size
print(group_size) SNP gene
8696600 43661 #estimated group PVE
estimated_group_pve <- estimated_group_pve_all[,ncol(group_prior_rec)]
print(estimated_group_pve) SNP gene
0.08761 0.02458 #total PVE
sum(estimated_group_pve)[1] 0.1122#attributable PVE
estimated_group_pve/sum(estimated_group_pve) SNP gene
0.7809 0.2191 Genes with highest PIPs
#distribution of PIPs
hist(ctwas_gene_res$susie_pip, xlim=c(0,1), main="Distribution of Gene PIPs")
| Version | Author | Date |
|---|---|---|
| 684d806 | sq-96 | 2023-01-26 |
#genes with PIP>0.8 or 20 highest PIPs
head(ctwas_gene_res[order(-ctwas_gene_res$susie_pip),report_cols], max(sum(ctwas_gene_res$susie_pip>0.8), 20)) genename region_tag id susie_pip mu2
21130 GCNT2 6_9 cg11118520 1.0000 7149.66
44652 ZBTB22 6_28 cg25191172 0.9909 177.59
10634 <NA> 6_24 cg05505711 0.9828 164.88
8001 <NA> 1_41 cg04111102 0.9647 174.01
30125 RP11-14C10.4 15_50 cg16103421 0.9630 35.05
21908 DPH1 17_2 cg11577151 0.9562 25.06
29469 AC034220.3;SLC22A5 5_79 cg15738769 0.9547 130.81
6808 <NA> 2_140 cg03472961 0.9519 34.00
11720 AC006126.4;MARK4 19_31 cg06112816 0.9502 270.67
36599 KDELC2 11_63 cg20058057 0.9450 29.64
17132 LYN 8_43 cg08894788 0.9424 50.17
44405 VLDLR;VLDLR-AS1 9_3 cg25032030 0.9251 46.75
39536 KDM4B 19_5 cg21973527 0.9241 30.75
46332 <NA> 18_11 cg26234723 0.9149 22.92
21856 PTPRJ 11_29 cg11545521 0.9130 69.71
16593 <NA> 11_74 cg08637269 0.8979 67.63
26543 <NA> 10_83 cg14138475 0.8942 35.35
45859 TTC39C 18_12 cg25952192 0.8834 32.18
33165 PAX8;PAX8-AS1;RP11-65I12.1 2_67 cg17774569 0.8816 36.18
34842 SPTLC2 14_36 cg18872420 0.8735 30.35
30365 ATXN7;THOC7 3_43 cg16258503 0.8589 24.00
35811 GPRIN3 4_60 cg19537443 0.8527 26.82
16511 SMG9 19_30 cg08581076 0.8489 34.87
44630 VAMP5 2_54 cg25178838 0.8165 37.39
34253 CD82 11_27 cg18496383 0.8147 24.35
38057 PADI1 1_12 cg21010178 0.8142 23.65
44782 <NA> 21_18 cg25269340 0.8139 60.02
32216 EHD4 15_15 cg17244218 0.8125 108.37
12790 GPR116 6_35 cg06673956 0.8107 33.74
PVE z num_eqtl
21130 2.040e-02 -3.928 1
44652 5.021e-04 9.566 1
10634 4.624e-04 -1.928 1
8001 4.790e-04 -16.175 1
30125 9.631e-05 5.765 1
21908 6.838e-05 -4.388 1
29469 3.563e-04 13.657 1
6808 9.236e-05 -7.559 1
11720 7.339e-04 14.933 1
36599 7.991e-05 -6.197 1
17132 1.349e-04 7.116 1
44405 1.234e-04 6.429 1
39536 8.108e-05 -5.487 1
46332 5.983e-05 -4.062 1
21856 1.816e-04 -9.930 1
16593 1.733e-04 8.437 1
26543 9.020e-05 -5.918 1
45859 8.112e-05 4.551 1
33165 9.101e-05 6.672 1
34842 7.563e-05 2.576 1
30365 5.882e-05 -4.033 1
35811 6.525e-05 -4.645 1
16511 8.447e-05 4.701 1
44630 8.712e-05 -5.035 1
34253 5.661e-05 4.524 1
38057 5.495e-05 -4.362 1
44782 1.394e-04 -7.733 1
32216 2.512e-04 -12.597 1
12790 7.805e-05 5.585 1Genes with largest effect sizes
#plot PIP vs effect size
plot(ctwas_gene_res$susie_pip, ctwas_gene_res$mu2, xlab="PIP", ylab="mu^2", main="Gene PIPs vs Effect Size")
| Version | Author | Date |
|---|---|---|
| 684d806 | sq-96 | 2023-01-26 |
#genes with 20 largest effect sizes
head(ctwas_gene_res[order(-ctwas_gene_res$mu2),report_cols],20) genename region_tag id susie_pip mu2 PVE z
41552 LSS 21_24 cg23289605 0 15995 0.0000 -4.8444
18868 LSS 21_24 cg09831081 0 13275 0.0000 -5.2615
22244 PCNT 21_24 cg11764399 0 9266 0.0000 4.5844
21130 GCNT2 6_9 cg11118520 1 7150 0.0204 -3.9282
26726 PCNT 21_24 cg14233374 0 6896 0.0000 4.9575
20725 PCNT 21_24 cg10878966 0 6314 0.0000 5.5785
5838 PCNT 21_24 cg02959939 0 6302 0.0000 5.5187
32742 HCP5;MICA 6_25 cg17529716 0 5615 0.0000 11.2491
18123 YBEY 21_24 cg09417038 0 5411 0.0000 -0.9051
23528 <NA> 21_24 cg12516959 0 5258 0.0000 -0.8848
1720 <NA> 21_24 cg00815214 0 5258 0.0000 -0.8848
43386 <NA> 6_25 cg24439364 0 4395 0.0000 10.8185
1282 <NA> 21_24 cg00612595 0 3936 0.0000 -0.9678
48178 HCP5;LINC01149 6_25 cg27326026 0 3767 0.0000 12.0717
32640 HCP5;MICA 6_25 cg17476405 0 3416 0.0000 14.4636
33606 LSS;MCM3AP-AS1 21_24 cg18069493 0 3406 0.0000 4.0912
14245 HCP5;MICA 6_25 cg07376033 0 3331 0.0000 11.7810
22003 PCNT 21_24 cg11628223 0 2979 0.0000 -1.7442
41 RNU6-1133P 6_25 cg00020172 0 2921 0.0000 -28.4773
47373 HCP5;MICA;Y_RNA 6_25 cg26846810 0 2850 0.0000 6.9007
num_eqtl
41552 1
18868 1
22244 1
21130 1
26726 1
20725 1
5838 1
32742 1
18123 1
23528 1
1720 1
43386 1
1282 1
48178 1
32640 1
33606 1
14245 1
22003 1
41 1
47373 1Genes with highest PVE
#genes with 20 highest pve
head(ctwas_gene_res[order(-ctwas_gene_res$PVE),report_cols],20) genename region_tag id susie_pip mu2 PVE
21130 GCNT2 6_9 cg11118520 1.0000 7149.66 0.0204002
14343 PSMD3 17_23 cg07427276 0.7984 622.59 0.0014183
11720 AC006126.4;MARK4 19_31 cg06112816 0.9502 270.67 0.0007339
24271 XXbac-BPG308K3.6 6_22 cg12914966 0.7554 321.11 0.0006921
44652 ZBTB22 6_28 cg25191172 0.9909 177.59 0.0005021
13981 CHD7 8_46 cg07228241 0.7942 212.30 0.0004811
8001 <NA> 1_41 cg04111102 0.9647 174.01 0.0004790
10634 <NA> 6_24 cg05505711 0.9828 164.88 0.0004624
29469 AC034220.3;SLC22A5 5_79 cg15738769 0.9547 130.81 0.0003563
9793 ZPBP2 17_23 cg05057505 0.6335 189.00 0.0003416
42089 MSH5;MSH5-SAPCD1 6_26 cg23634079 0.3764 309.02 0.0003319
30848 C2;ZBTB12 6_26 cg16505946 0.3764 309.02 0.0003319
46716 <NA> 17_23 cg26458775 0.1714 619.42 0.0003030
29677 PREX1 20_30 cg15849237 0.6005 162.21 0.0002780
32216 EHD4 15_15 cg17244218 0.8125 108.37 0.0002512
21856 PTPRJ 11_29 cg11545521 0.9130 69.71 0.0001816
16593 <NA> 11_74 cg08637269 0.8979 67.63 0.0001733
38255 PREX1 20_30 cg21145944 0.3599 163.39 0.0001678
47128 REST 4_41 cg26694713 0.7433 78.03 0.0001655
4819 PAK2;U4 3_121 cg02455773 0.5334 106.62 0.0001623
z num_eqtl
21130 -3.928 1
14343 -37.218 1
11720 14.933 1
24271 19.798 1
44652 9.566 1
13981 2.826 1
8001 -16.175 1
10634 -1.928 1
29469 13.657 1
9793 23.719 1
42089 26.924 1
30848 -26.924 1
46716 -37.059 1
29677 -2.590 1
32216 -12.597 1
21856 -9.930 1
16593 8.437 1
38255 2.394 1
47128 -9.062 1
4819 9.125 1Genes with largest z scores
#genes with 20 largest z scores
head(ctwas_gene_res[order(-abs(ctwas_gene_res$z)),report_cols],20) genename region_tag id susie_pip mu2
14343 PSMD3 17_23 cg07427276 7.984e-01 622.6
46716 <NA> 17_23 cg26458775 1.714e-01 619.4
32508 MED24;THRA 17_23 cg17401724 4.598e-10 406.2
31946 HLA-C 6_25 cg17096289 0.000e+00 846.3
41 RNU6-1133P 6_25 cg00020172 0.000e+00 2920.5
6981 MED24;MIR6884 17_23 cg03568305 6.590e-10 350.2
6598 MED24;MIR6884 17_23 cg03367679 6.590e-10 350.2
9762 TNXB 6_26 cg05045332 1.110e-16 417.9
11743 <NA> 17_23 cg06123174 8.195e-08 294.0
9784 APOM;BAG6 6_26 cg05053818 0.000e+00 445.5
46204 GSDMA 17_23 cg26162295 6.643e-11 262.9
26619 SKIV2L 6_26 cg14178705 0.000e+00 420.5
44201 GSDMA 17_23 cg24910161 5.043e-11 237.5
18438 HLA-B;HLA-C;XXbac-BPG248L24.12 6_25 cg09588770 0.000e+00 858.0
42089 MSH5;MSH5-SAPCD1 6_26 cg23634079 3.764e-01 309.0
30848 C2;ZBTB12 6_26 cg16505946 3.764e-01 309.0
13216 BTNL2 6_26 cg06871764 0.000e+00 397.3
44275 <NA> 6_26 cg24965496 0.000e+00 446.6
31319 HLA-DRA 6_26 cg16753237 0.000e+00 300.2
39715 <NA> 6_25 cg22110654 6.433e-10 796.6
PVE z num_eqtl
14343 1.418e-03 -37.22 1
46716 3.030e-04 -37.06 1
32508 5.330e-13 -30.92 1
31946 0.000e+00 28.80 1
41 0.000e+00 -28.48 1
6981 6.584e-13 28.44 1
6598 6.584e-13 28.44 1
9762 1.324e-19 -28.30 1
11743 6.875e-11 28.01 1
9784 0.000e+00 27.89 1
46204 4.983e-14 -27.87 1
26619 0.000e+00 -27.59 1
44201 3.418e-14 -27.47 1
18438 0.000e+00 27.12 1
42089 3.319e-04 26.92 1
30848 3.319e-04 -26.92 1
13216 0.000e+00 26.79 1
44275 0.000e+00 26.43 1
31319 0.000e+00 26.11 1
39715 1.462e-12 -25.85 1Comparing z scores and PIPs
#set nominal signifiance threshold for z scores
alpha <- 0.05
#bonferroni adjusted threshold for z scores
sig_thresh <- qnorm(1-(alpha/nrow(ctwas_gene_res)/2), lower=T)
#Q-Q plot for z scores
obs_z <- ctwas_gene_res$z[order(ctwas_gene_res$z)]
exp_z <- qnorm((1:nrow(ctwas_gene_res))/nrow(ctwas_gene_res))
plot(exp_z, obs_z, xlab="Expected z", ylab="Observed z", main="Gene z score Q-Q plot")
abline(a=0,b=1)
| Version | Author | Date |
|---|---|---|
| 684d806 | sq-96 | 2023-01-26 |
#plot z score vs PIP
plot(abs(ctwas_gene_res$z), ctwas_gene_res$susie_pip, xlab="abs(z)", ylab="PIP")
abline(v=sig_thresh, col="red", lty=2)
| Version | Author | Date |
|---|---|---|
| 684d806 | sq-96 | 2023-01-26 |
#number of significant z scores
sum(abs(ctwas_gene_res$z) > sig_thresh)[1] 1431#proportion of significant z scores
mean(abs(ctwas_gene_res$z) > sig_thresh)[1] 0.03278#genes with most significant z scores
head(ctwas_gene_res[order(-abs(ctwas_gene_res$z)),report_cols],20) genename region_tag id susie_pip mu2
14343 PSMD3 17_23 cg07427276 7.984e-01 622.6
46716 <NA> 17_23 cg26458775 1.714e-01 619.4
32508 MED24;THRA 17_23 cg17401724 4.598e-10 406.2
31946 HLA-C 6_25 cg17096289 0.000e+00 846.3
41 RNU6-1133P 6_25 cg00020172 0.000e+00 2920.5
6981 MED24;MIR6884 17_23 cg03568305 6.590e-10 350.2
6598 MED24;MIR6884 17_23 cg03367679 6.590e-10 350.2
9762 TNXB 6_26 cg05045332 1.110e-16 417.9
11743 <NA> 17_23 cg06123174 8.195e-08 294.0
9784 APOM;BAG6 6_26 cg05053818 0.000e+00 445.5
46204 GSDMA 17_23 cg26162295 6.643e-11 262.9
26619 SKIV2L 6_26 cg14178705 0.000e+00 420.5
44201 GSDMA 17_23 cg24910161 5.043e-11 237.5
18438 HLA-B;HLA-C;XXbac-BPG248L24.12 6_25 cg09588770 0.000e+00 858.0
42089 MSH5;MSH5-SAPCD1 6_26 cg23634079 3.764e-01 309.0
30848 C2;ZBTB12 6_26 cg16505946 3.764e-01 309.0
13216 BTNL2 6_26 cg06871764 0.000e+00 397.3
44275 <NA> 6_26 cg24965496 0.000e+00 446.6
31319 HLA-DRA 6_26 cg16753237 0.000e+00 300.2
39715 <NA> 6_25 cg22110654 6.433e-10 796.6
PVE z num_eqtl
14343 1.418e-03 -37.22 1
46716 3.030e-04 -37.06 1
32508 5.330e-13 -30.92 1
31946 0.000e+00 28.80 1
41 0.000e+00 -28.48 1
6981 6.584e-13 28.44 1
6598 6.584e-13 28.44 1
9762 1.324e-19 -28.30 1
11743 6.875e-11 28.01 1
9784 0.000e+00 27.89 1
46204 4.983e-14 -27.87 1
26619 0.000e+00 -27.59 1
44201 3.418e-14 -27.47 1
18438 0.000e+00 27.12 1
42089 3.319e-04 26.92 1
30848 3.319e-04 -26.92 1
13216 0.000e+00 26.79 1
44275 0.000e+00 26.43 1
31319 0.000e+00 26.11 1
39715 1.462e-12 -25.85 1SNPs with highest PIPs
#snps with PIP>0.8 or 20 highest PIPs
head(ctwas_snp_res[order(-ctwas_snp_res$susie_pip),report_cols_snps],
max(sum(ctwas_snp_res$susie_pip>0.8), 20)) id region_tag id.1 susie_pip mu2 PVE
31705 rs6679677 1_70 rs6679677 1.0000 146.55 4.182e-04
58478 rs10803164 1_122 rs10803164 1.0000 186.85 5.331e-04
62820 rs12239046 1_131 rs12239046 1.0000 99.44 2.837e-04
115498 rs3835963 2_110 rs3835963 1.0000 107.56 3.069e-04
218483 rs1371794 4_51 rs1371794 1.0000 476.03 1.358e-03
221306 rs529050451 4_56 rs529050451 1.0000 708.60 2.022e-03
377037 rs56388170 7_24 rs56388170 1.0000 369.05 1.053e-03
396284 rs79912251 7_56 rs79912251 1.0000 145.07 4.139e-04
628523 rs79490353 13_7 rs79490353 1.0000 192.35 5.488e-04
777917 rs12461480 19_4 rs12461480 1.0000 215.36 6.145e-04
825443 rs13049759 21_24 rs13049759 1.0000 19341.21 5.519e-02
825445 rs13049893 21_24 rs13049893 1.0000 19430.21 5.544e-02
868195 rs34599082 1_78 rs34599082 1.0000 177.67 5.070e-04
934104 rs200599211 5_79 rs200599211 1.0000 1818.82 5.190e-03
979576 rs201369106 6_25 rs201369106 1.0000 12076.72 3.446e-02
1147212 rs4760 19_30 rs4760 1.0000 307.26 8.767e-04
72545 rs780093 2_16 rs780093 1.0000 137.29 3.917e-04
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397773 -5.9039
695299 -8.5754
678759 5.8530
125689 -6.1809
368103 7.1263
475470 -4.5565
206382 6.3327
483938 -7.2362
396361 -5.2273
2809 7.3965
77564 4.2466
82036 5.6673
697841 -5.1295
1090478 6.6352
753564 5.3438
798683 -5.4026
171334 -6.2026
546677 -5.7716
188427 4.6439
34996 5.7613
868196 -4.9802
154686 -5.4082
377034 7.7822
309184 5.1875
742719 5.8237
896157 6.9180
775807 4.7579
580061 -10.0269
748603 4.7536
7235 -6.2659
105084 -8.7371
115491 8.2415
666760 -4.7561
442541 -9.4469
742575 7.4417
597984 -5.5136
868188 -4.8708
134685 -4.7395
572215 6.2129
78782 5.2992
787395 5.1593
634076 4.6345
399732 4.8593
850036 4.3921
35287 -8.1097
658620 10.8893
655446 -4.9404
717874 5.2069
557710 -5.3299
1157394 6.9349
314121 5.5926
407931 -5.5257
619609 -5.3471
952042 -9.7257
456525 5.3060
58154 7.0545
729892 -5.3814
794200 4.5892
207362 7.4784
339574 -7.5075
535580 -5.0133
320571 -5.8011
731521 5.4841
620644 6.4063
48861 -5.3338
49375 10.2518
952603 8.5058
484266 -4.4269
464528 -6.5608
607240 -5.2670
217915 -8.0809
412146 4.9752
318103 4.1644
582018 -4.5946
779131 -8.0320
319081 -4.7844
598993 4.6105
422373 6.6410
530143 -4.4662
928994 -7.6381
318840 5.0209
711583 3.8732
738239 -8.3444
292988 -7.5808
825829 4.4313
746647 -5.7245
457606 -6.9790
464562 7.5243
457053 7.7217
321001 29.7491
813816 -4.8715
602942 6.8687
398310 -3.9742
921317 -6.1001
296486 -4.8858
497862 5.2746
586594 4.5310
457588 -6.2508
72570 3.3681
780093 -9.5115
502035 4.8594
367656 5.3596
724897 4.7348
421968 3.0103
783175 4.2712
5312 4.8663
690873 4.7005
690811 -2.9983
227861 -4.4658
207140 -4.4771
87324 -5.2861
782104 -9.2524
731657 -5.6078
828058 -5.3105
93325 5.5006
853117 12.7746
85826 4.9226
77911 -6.1157
313944 4.5511
814782 5.1986
344433 4.7105
396281 4.9715
734864 4.3527
20691 4.5431
283260 -4.8603
375253 6.5229
147697 -10.1402
808621 1.4297
115481 -1.8327
807298 -4.6724
322383 4.3281
840087 -6.3056
396277 -11.6557
948922 -0.3897
604512 -4.7285
703724 -4.5188
26249 4.8992
273793 -5.0365
644248 -4.5407
617064 -7.5514
603694 -5.3758
789513 8.2187
521631 -5.4996
895772 -6.3367
161893 5.2481
193168 5.1512
695427 -4.5684
746953 7.6171
38224 -4.3837
994761 11.7187
510448 11.5079
318422 -5.4925
368758 -6.4972
741296 4.5802
825907 5.0353
188346 -4.0308
464217 -4.1988
188464 -4.5603
955192 5.8186
797951 -3.8163
274626 5.9971
539260 5.9897SNPs with largest effect sizes
#plot PIP vs effect size
#plot(ctwas_snp_res$susie_pip, ctwas_snp_res$mu2, xlab="PIP", ylab="mu^2", main="SNP PIPs vs Effect Size")
#SNPs with 50 largest effect sizes
head(ctwas_snp_res[order(-ctwas_snp_res$mu2),report_cols_snps],50) id region_tag id.1 susie_pip mu2 PVE z
825445 rs13049893 21_24 rs13049893 1.000e+00 19430 5.544e-02 4.818
825443 rs13049759 21_24 rs13049759 1.000e+00 19341 5.519e-02 4.970
825430 rs13052701 21_24 rs13052701 0.000e+00 16370 0.000e+00 4.944
825433 rs147757092 21_24 rs147757092 0.000e+00 14934 0.000e+00 4.614
825476 rs11702800 21_24 rs11702800 0.000e+00 14349 0.000e+00 -5.560
825489 rs2268523 21_24 rs2268523 0.000e+00 14313 0.000e+00 -5.586
825486 rs9981445 21_24 rs9981445 0.000e+00 14077 0.000e+00 -5.570
825506 rs2839257 21_24 rs2839257 0.000e+00 13981 0.000e+00 -5.710
825470 rs11909986 21_24 rs11909986 0.000e+00 12579 0.000e+00 6.006
825424 rs35679325 21_24 rs35679325 0.000e+00 12250 0.000e+00 -5.090
825441 rs4819221 21_24 rs4819221 0.000e+00 12208 0.000e+00 5.060
979573 rs3869130 6_25 rs3869130 3.125e-01 12143 1.083e-02 14.055
979574 rs3869131 6_25 rs3869131 1.870e-01 12143 6.479e-03 14.047
979570 rs3899823 6_25 rs3899823 4.284e-01 12142 1.484e-02 14.063
979586 rs34259803 6_25 rs34259803 4.423e-02 12140 1.532e-03 14.034
979571 rs3869129 6_25 rs3869129 2.788e-02 12136 9.653e-04 14.056
825449 rs4818832 21_24 rs4818832 0.000e+00 12119 0.000e+00 5.082
825448 rs62226478 21_24 rs62226478 0.000e+00 12116 0.000e+00 5.087
979563 rs73404245 6_25 rs73404245 5.850e-08 12100 2.020e-09 13.998
825446 rs34586434 21_24 rs34586434 0.000e+00 12094 0.000e+00 5.094
979576 rs201369106 6_25 rs201369106 1.000e+00 12077 3.446e-02 1.719
979582 rs7769942 6_25 rs7769942 8.882e-16 11984 3.037e-17 14.605
979560 rs566631013 6_25 rs566631013 0.000e+00 11108 0.000e+00 12.820
979558 rs373478096 6_25 rs373478096 0.000e+00 11108 0.000e+00 12.820
979559 rs200256874 6_25 rs200256874 0.000e+00 11108 0.000e+00 12.820
825437 rs2032226 21_24 rs2032226 0.000e+00 10457 0.000e+00 5.361
825431 rs4535149 21_24 rs4535149 0.000e+00 10369 0.000e+00 5.360
979218 rs9501109 6_25 rs9501109 0.000e+00 10123 0.000e+00 16.607
825421 rs2001809 21_24 rs2001809 0.000e+00 9906 0.000e+00 3.733
979285 rs60539855 6_25 rs60539855 0.000e+00 9532 0.000e+00 16.465
979652 rs4458721 6_25 rs4458721 0.000e+00 9423 0.000e+00 16.419
979588 rs73404265 6_25 rs73404265 0.000e+00 9172 0.000e+00 13.695
979581 rs7769403 6_25 rs7769403 0.000e+00 9171 0.000e+00 13.693
825426 rs4819218 21_24 rs4819218 0.000e+00 8965 0.000e+00 4.926
825425 rs2280959 21_24 rs2280959 0.000e+00 8953 0.000e+00 4.934
825511 rs2073381 21_24 rs2073381 0.000e+00 8897 0.000e+00 4.936
979330 rs117813801 6_25 rs117813801 0.000e+00 8779 0.000e+00 13.870
979360 rs114921825 6_25 rs114921825 0.000e+00 8779 0.000e+00 13.705
979331 rs143741838 6_25 rs143741838 0.000e+00 8779 0.000e+00 13.871
979355 rs4090415 6_25 rs4090415 0.000e+00 8774 0.000e+00 13.768
979353 rs4090417 6_25 rs4090417 0.000e+00 8773 0.000e+00 13.767
979354 rs4090416 6_25 rs4090416 0.000e+00 8773 0.000e+00 13.767
979351 rs9501116 6_25 rs9501116 0.000e+00 8773 0.000e+00 13.764
979350 rs9501115 6_25 rs9501115 0.000e+00 8772 0.000e+00 13.765
979555 rs28575156 6_25 rs28575156 0.000e+00 8768 0.000e+00 13.707
979388 rs2394999 6_25 rs2394999 0.000e+00 8765 0.000e+00 13.725
979382 rs2894212 6_25 rs2894212 0.000e+00 8765 0.000e+00 13.727
979384 rs4631325 6_25 rs4631325 0.000e+00 8765 0.000e+00 13.727
979387 rs2394998 6_25 rs2394998 0.000e+00 8765 0.000e+00 13.725
979380 rs80339222 6_25 rs80339222 0.000e+00 8765 0.000e+00 13.726SNPs with highest PVE
#SNPs with 50 highest pve
head(ctwas_snp_res[order(-ctwas_snp_res$PVE),report_cols_snps],50) id region_tag id.1 susie_pip mu2 PVE z
825445 rs13049893 21_24 rs13049893 1.00000 19430.2 0.0554404 4.8177
825443 rs13049759 21_24 rs13049759 1.00000 19341.2 0.0551865 4.9695
979576 rs201369106 6_25 rs201369106 1.00000 12076.7 0.0344586 1.7190
948922 rs112655417 6_9 rs112655417 0.83369 6892.4 0.0163954 -0.3897
979570 rs3899823 6_25 rs3899823 0.42840 12142.4 0.0148423 14.0629
948881 rs470863 6_9 rs470863 0.56473 6885.3 0.0110945 -0.4829
979573 rs3869130 6_25 rs3869130 0.31250 12143.2 0.0108276 14.0552
948894 rs470562 6_9 rs470562 0.41950 6885.7 0.0082420 -0.4744
979574 rs3869131 6_25 rs3869131 0.18699 12143.2 0.0064790 14.0471
974399 rs2524079 6_25 rs2524079 1.00000 2259.5 0.0064472 32.3917
934104 rs200599211 5_79 rs200599211 1.00000 1818.8 0.0051897 2.4536
980873 rs2229094 6_25 rs2229094 0.99999 1485.7 0.0042392 19.4379
979803 rs9267123 6_25 rs9267123 1.00000 869.1 0.0024797 -28.1821
948948 rs112850802 6_9 rs112850802 0.12491 6876.9 0.0024510 -0.3953
221306 rs529050451 4_56 rs529050451 1.00000 708.6 0.0020219 1.6324
617055 rs653178 12_67 rs653178 0.99999 573.8 0.0016371 -26.3817
979586 rs34259803 6_25 rs34259803 0.04423 12140.2 0.0015322 14.0343
218483 rs1371794 4_51 rs1371794 1.00000 476.0 0.0013583 -23.3384
321001 rs9391881 6_26 rs9391881 0.90152 520.4 0.0013388 29.7491
377037 rs56388170 7_24 rs56388170 1.00000 369.0 0.0010530 20.7223
979571 rs3869129 6_25 rs3869129 0.02788 12135.9 0.0009653 14.0556
221253 rs6814526 4_56 rs6814526 0.99979 309.1 0.0008818 -12.5319
1147212 rs4760 19_30 rs4760 1.00000 307.3 0.0008767 -17.9363
221309 rs9654217 4_56 rs9654217 0.42939 712.0 0.0008723 7.1517
221310 rs9654218 4_56 rs9654218 0.42509 712.0 0.0008636 7.1513
320525 rs2736155 6_26 rs2736155 0.99854 279.5 0.0007964 20.5510
437157 rs4738814 8_46 rs4738814 1.00000 235.4 0.0006717 -10.8946
969543 rs1264349 6_24 rs1264349 0.45458 502.0 0.0006511 -24.7873
958381 rs1233380 6_23 rs1233380 1.00000 223.4 0.0006376 19.2276
320477 rs67040724 6_21 rs67040724 0.71988 307.4 0.0006315 -18.4527
777917 rs12461480 19_4 rs12461480 1.00000 215.4 0.0006145 -7.6886
9489 rs3917932 1_22 rs3917932 1.00000 209.9 0.0005990 -15.8760
934118 rs13361914 5_79 rs13361914 0.10966 1809.9 0.0005663 -1.7542
1030785 rs14408 11_1 rs14408 0.99545 194.5 0.0005525 15.8381
934125 rs77753417 5_79 rs77753417 0.10675 1809.9 0.0005513 -1.7544
628523 rs79490353 13_7 rs79490353 1.00000 192.4 0.0005488 11.9357
321991 rs41258084 6_27 rs41258084 1.00000 189.9 0.0005419 12.3107
58478 rs10803164 1_122 rs10803164 1.00000 186.8 0.0005331 -14.3656
353114 rs56293029 6_89 rs56293029 0.60434 305.0 0.0005260 -16.9971
934121 rs113694337 5_79 rs113694337 0.10124 1809.8 0.0005228 -1.7519
509026 rs112955547 10_18 rs112955547 0.47367 385.0 0.0005203 -18.4434
969114 rs3131063 6_24 rs3131063 0.99952 180.9 0.0005158 -11.0071
868195 rs34599082 1_78 rs34599082 1.00000 177.7 0.0005070 -14.0113
321920 rs9276625 6_27 rs9276625 0.54185 327.5 0.0005064 -20.9363
958798 rs3131894 6_23 rs3131894 0.55281 314.4 0.0004960 -23.1028
320571 rs115487693 6_26 rs115487693 0.93719 182.6 0.0004882 -5.8011
948952 rs72819781 6_9 rs72819781 0.02476 6862.6 0.0004848 -0.4151
777908 rs2041128 19_4 rs2041128 0.99993 163.6 0.0004668 -1.1756
320540 rs1266074 6_26 rs1266074 0.99997 160.6 0.0004581 13.1014
963740 rs9260620 6_24 rs9260620 0.56272 276.7 0.0004442 -21.7153SNPs with largest z scores
#histogram of (abs) SNP z scores
hist(abs(ctwas_snp_res$z))
| Version | Author | Date |
|---|---|---|
| 684d806 | sq-96 | 2023-01-26 |
#SNPs with 50 largest z scores
head(ctwas_snp_res[order(-abs(ctwas_snp_res$z)),report_cols_snps],50) id region_tag id.1 susie_pip mu2 PVE z
1108383 rs8078723 17_23 rs8078723 2.011e-03 608.4 3.491e-06 37.33
1108420 rs709592 17_23 rs709592 2.349e-03 609.6 4.085e-06 37.32
1108421 rs709591 17_23 rs709591 1.994e-03 608.9 3.465e-06 37.31
1108375 rs55771023 17_23 rs55771023 1.504e-03 607.4 2.607e-06 37.30
1108374 rs55736351 17_23 rs55736351 1.422e-03 607.2 2.463e-06 37.30
1108339 rs4795414 17_23 rs4795414 1.028e-03 605.6 1.776e-06 37.30
1108340 rs4795415 17_23 rs4795415 1.026e-03 605.6 1.774e-06 37.30
1108341 rs4795416 17_23 rs4795416 1.021e-03 605.5 1.765e-06 37.30
1108350 rs8065519 17_23 rs8065519 1.019e-03 605.6 1.760e-06 37.30
1108335 rs56922390 17_23 rs56922390 9.628e-04 605.3 1.663e-06 37.29
1108361 rs12602172 17_23 rs12602172 9.388e-04 605.5 1.622e-06 37.29
1108334 rs4794822 17_23 rs4794822 8.848e-04 605.1 1.528e-06 37.29
1108369 rs55846942 17_23 rs55846942 9.324e-04 605.5 1.611e-06 37.29
1108359 rs12600856 17_23 rs12600856 9.182e-04 605.4 1.586e-06 37.29
1108380 rs4795419 17_23 rs4795419 9.409e-04 605.6 1.626e-06 37.29
1108381 rs4794823 17_23 rs4794823 8.888e-04 605.4 1.535e-06 37.29
1108353 rs8070454 17_23 rs8070454 8.040e-04 604.9 1.388e-06 37.29
1108372 rs4795418 17_23 rs4795418 8.301e-04 605.2 1.433e-06 37.29
1108355 rs6503530 17_23 rs6503530 7.779e-04 604.8 1.342e-06 37.28
1108376 rs7221894 17_23 rs7221894 7.095e-04 604.6 1.224e-06 37.28
1108417 rs2227336 17_23 rs2227336 6.848e-04 604.9 1.182e-06 37.27
1108404 rs2227322 17_23 rs2227322 6.025e-04 604.4 1.039e-06 37.27
1108415 rs1042658 17_23 rs1042658 6.174e-04 604.5 1.065e-06 37.27
1108425 rs11871747 17_23 rs11871747 5.111e-04 605.3 8.826e-07 37.26
1108393 rs7208815 17_23 rs7208815 5.882e-04 604.3 1.014e-06 37.26
1108386 rs4795420 17_23 rs4795420 4.990e-04 603.6 8.594e-07 37.26
1108385 rs62065177 17_23 rs62065177 4.922e-04 603.5 8.477e-07 37.26
1108395 rs7214085 17_23 rs7214085 4.746e-04 603.4 8.172e-07 37.26
1108390 rs57065891 17_23 rs57065891 4.714e-04 603.4 8.117e-07 37.26
1108398 rs59925331 17_23 rs59925331 4.691e-04 603.4 8.076e-07 37.26
1108399 rs2227315 17_23 rs2227315 4.407e-04 603.2 7.584e-07 37.25
1108326 rs7021 17_23 rs7021 3.290e-04 601.4 5.646e-07 37.24
1108317 rs4795412 17_23 rs4795412 2.895e-04 600.8 4.963e-07 37.23
1108330 rs8081692 17_23 rs8081692 2.921e-04 601.0 5.010e-07 37.23
1108293 rs57968500 17_23 rs57968500 2.284e-04 599.5 3.907e-07 37.22
1108432 rs4794824 17_23 rs4794824 1.008e-04 600.6 1.727e-07 37.13
1108430 rs3213762 17_23 rs3213762 2.695e-05 595.3 4.578e-08 37.07
1108356 rs111848559 17_23 rs111848559 5.049e-05 596.4 8.592e-08 37.06
1108447 rs6503533 17_23 rs6503533 1.088e-05 605.6 1.879e-08 -36.96
1108316 rs3826331 17_23 rs3826331 3.769e-09 580.5 6.242e-12 -36.93
1108418 rs1045929 17_23 rs1045929 1.595e-06 586.9 2.671e-09 36.89
1108304 rs60666652 17_23 rs60666652 2.155e-07 582.8 3.583e-10 36.72
1108303 rs60082402 17_23 rs60082402 2.021e-07 582.6 3.360e-10 36.72
1108389 rs60005225 17_23 rs60005225 4.537e-08 577.5 7.476e-11 36.67
1108347 rs12941811 17_23 rs12941811 7.362e-12 582.0 1.222e-14 -36.55
1108321 rs8070444 17_23 rs8070444 3.087e-11 578.5 5.095e-14 -35.99
1108289 rs12450688 17_23 rs12450688 3.433e-11 581.0 5.691e-14 -35.98
1108272 rs2305482 17_23 rs2305482 4.329e-11 583.2 7.204e-14 -35.98
1108322 rs8071037 17_23 rs8071037 2.883e-11 576.9 4.746e-14 -35.97
1108292 rs9915252 17_23 rs9915252 3.184e-11 579.3 5.263e-14 -35.96
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 generics_0.1.3
[5] colorspace_2.0-3 vctrs_0.5.1 htmltools_0.5.4 yaml_2.3.6
[9] utf8_1.2.2 blob_1.2.3 rlang_1.0.6 jquerylib_0.1.4
[13] later_1.3.0 pillar_1.8.1 withr_2.5.0 glue_1.6.2
[17] DBI_1.1.3 bit64_4.0.5 lifecycle_1.0.3 stringr_1.5.0
[21] munsell_0.5.0 gtable_0.3.1 evaluate_0.19 memoise_2.0.1
[25] labeling_0.4.2 knitr_1.41 callr_3.7.3 fastmap_1.1.0
[29] httpuv_1.6.7 ps_1.7.2 fansi_1.0.3 highr_0.9
[33] Rcpp_1.0.9 promises_1.2.0.1 scales_1.2.1 cachem_1.0.6
[37] jsonlite_1.8.4 farver_2.1.0 fs_1.5.2 bit_4.0.5
[41] digest_0.6.31 stringi_1.7.8 processx_3.8.0 dplyr_1.0.10
[45] getPass_0.2-2 rprojroot_2.0.3 grid_4.1.0 cli_3.4.1
[49] tools_4.1.0 magrittr_2.0.3 sass_0.4.4 tibble_3.1.8
[53] RSQLite_2.2.19 whisker_0.4.1 pkgconfig_2.0.3 data.table_1.14.6
[57] assertthat_0.2.1 rmarkdown_2.19 httr_1.4.4 rstudioapi_0.14
[61] R6_2.5.1 git2r_0.30.1 compiler_4.1.0