LDL - Liver
sheng Qian
2022-10-18
Last updated: 2023-01-23
Checks: 5 2
Knit directory: cTWAS_analysis/
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| Rmd | 4d68754 | sq-96 | 2023-01-23 | update |
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Weight QC
[1] 11502[1] 3159
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
303 212 161 125 140 200 169 111 120 118 187 178 52 100 102 172 194 47 238 91
21 22
45 94 [1] 1Load ctwas results
Check convergence of parameters
| Version | Author | Date |
|---|---|---|
| 4d68754 | sq-96 | 2023-01-23 |
#estimated group prior
estimated_group_prior <- estimated_group_prior_all[,ncol(group_prior_rec)]
print(estimated_group_prior) SNP gene
0.0001823 0.0173883 #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
11.07 52.98 #estimated enrichment
estimated_enrichment <- estimated_enrichment_all[ncol(group_prior_var_rec)]
print(estimated_enrichment)[1] 95.41#report sample size
print(sample_size)[1] 343621#report group size
print(group_size) SNP gene
8696600 3159 #estimated group PVE
estimated_group_pve <- estimated_group_pve_all[,ncol(group_prior_rec)]
print(estimated_group_pve) SNP gene
0.051055 0.008469 #total PVE
sum(estimated_group_pve)[1] 0.05952#attributable PVE
estimated_group_pve/sum(estimated_group_pve) SNP gene
0.8577 0.1423 Genes with highest PIPs
#distribution of PIPs
hist(ctwas_gene_res$susie_pip, xlim=c(0,1), main="Distribution of Gene PIPs")
| Version | Author | Date |
|---|---|---|
| 4d68754 | sq-96 | 2023-01-23 |
#genes with PIP>0.8 or 20 highest PIPs
head(ctwas_gene_res[order(-ctwas_gene_res$susie_pip),report_cols], max(sum(ctwas_gene_res$susie_pip>0.8), 20)) genename region_tag susie_pip mu2 PVE z num_eqtl
4433 PSRC1 1_67 1.0000 1676.75 4.880e-03 -41.687 1
11327 HPR 16_38 1.0000 452.14 1.316e-03 -16.590 1
NA.365 <NA> 1_121 0.9997 204.92 5.962e-04 -15.108 1
4315 ANGPTL3 1_39 0.9964 251.54 7.294e-04 16.132 1
8523 TNKS 8_12 0.9955 77.42 2.243e-04 10.918 1
5988 FADS1 11_34 0.9952 156.60 4.536e-04 12.587 1
1597 PLTP 20_28 0.9920 61.78 1.784e-04 -5.732 1
10708 NYNRIN 14_3 0.9917 58.17 1.679e-04 7.679 1
9365 GAS6 13_62 0.9908 71.37 2.058e-04 -8.924 1
2092 SP4 7_19 0.9807 103.07 2.941e-04 10.693 1
6090 CSNK1G3 5_75 0.9800 84.95 2.423e-04 9.116 1
6774 PKN3 9_66 0.9791 48.00 1.368e-04 -6.621 1
11257 CYP2A6 19_28 0.9757 32.76 9.303e-05 5.407 1
9251 ZNF329 19_39 0.9695 107.38 3.030e-04 10.059 1
2454 ST3GAL4 11_77 0.9508 82.25 2.276e-04 11.943 1
9046 KLHDC7A 1_13 0.8879 21.57 5.573e-05 4.124 1
6615 TMED4 7_32 0.8801 55.44 1.420e-04 9.455 1
3720 INSIG2 2_69 0.8789 45.34 1.160e-04 -6.998 1
9054 SPTY2D1 11_13 0.8656 33.81 8.518e-05 -5.557 1
6097 ALLC 2_2 0.8554 28.16 7.009e-05 4.919 1
1309 FMO2 1_84 0.8521 27.55 6.832e-05 4.821 1Genes with largest effect sizes
#plot PIP vs effect size
plot(ctwas_gene_res$susie_pip, ctwas_gene_res$mu2, xlab="PIP", ylab="mu^2", main="Gene PIPs vs Effect Size")
#genes with 20 largest effect sizes
head(ctwas_gene_res[order(-ctwas_gene_res$mu2),report_cols],20) genename region_tag susie_pip mu2 PVE z num_eqtl
5797 SLC22A3 6_104 0.000e+00 6380.59 0.000e+00 -6.593 1
10399 LPA 6_104 0.000e+00 1997.74 0.000e+00 8.120 1
4433 PSRC1 1_67 1.000e+00 1676.75 4.880e-03 -41.687 1
11327 HPR 16_38 1.000e+00 452.14 1.316e-03 -16.590 1
NA.122 <NA> 6_104 0.000e+00 353.45 0.000e+00 -8.475 1
4315 ANGPTL3 1_39 9.964e-01 251.54 7.294e-04 16.132 1
NA.159 <NA> 8_83 4.677e-03 243.37 3.313e-06 14.404 1
NA.365 <NA> 1_121 9.997e-01 204.92 5.962e-04 -15.108 1
11471 PKD1L3 16_38 2.693e-06 176.63 1.384e-09 4.999 1
5988 FADS1 11_34 9.952e-01 156.60 4.536e-04 12.587 1
9251 ZNF329 19_39 9.695e-01 107.38 3.030e-04 10.059 1
2092 SP4 7_19 9.807e-01 103.07 2.941e-04 10.693 1
781 PVR 19_31 0.000e+00 102.05 0.000e+00 -3.544 1
9910 RHCE 1_18 4.153e-01 101.60 1.228e-04 10.264 1
4047 NECTIN2 19_31 0.000e+00 100.08 0.000e+00 5.825 1
9718 CEACAM19 19_31 0.000e+00 99.39 0.000e+00 -10.909 1
9428 TMEM50A 1_18 8.126e-02 98.23 2.323e-05 10.082 1
2309 KPNB1 17_27 3.386e-01 98.00 9.656e-05 -9.909 1
9438 EMILIN3 20_25 2.540e-02 93.34 6.901e-06 9.502 1
6090 CSNK1G3 5_75 9.800e-01 84.95 2.423e-04 9.116 1Genes with highest PVE
#genes with 20 highest pve
head(ctwas_gene_res[order(-ctwas_gene_res$PVE),report_cols],20) genename region_tag susie_pip mu2 PVE z num_eqtl
4433 PSRC1 1_67 1.0000 1676.75 4.880e-03 -41.687 1
11327 HPR 16_38 1.0000 452.14 1.316e-03 -16.590 1
4315 ANGPTL3 1_39 0.9964 251.54 7.294e-04 16.132 1
NA.365 <NA> 1_121 0.9997 204.92 5.962e-04 -15.108 1
5988 FADS1 11_34 0.9952 156.60 4.536e-04 12.587 1
9251 ZNF329 19_39 0.9695 107.38 3.030e-04 10.059 1
2092 SP4 7_19 0.9807 103.07 2.941e-04 10.693 1
6090 CSNK1G3 5_75 0.9800 84.95 2.423e-04 9.116 1
2454 ST3GAL4 11_77 0.9508 82.25 2.276e-04 11.943 1
8523 TNKS 8_12 0.9955 77.42 2.243e-04 10.918 1
9365 GAS6 13_62 0.9908 71.37 2.058e-04 -8.924 1
1597 PLTP 20_28 0.9920 61.78 1.784e-04 -5.732 1
10708 NYNRIN 14_3 0.9917 58.17 1.679e-04 7.679 1
6615 TMED4 7_32 0.8801 55.44 1.420e-04 9.455 1
6774 PKN3 9_66 0.9791 48.00 1.368e-04 -6.621 1
9910 RHCE 1_18 0.4153 101.60 1.228e-04 10.264 1
3720 INSIG2 2_69 0.8789 45.34 1.160e-04 -6.998 1
2309 KPNB1 17_27 0.3386 98.00 9.656e-05 -9.909 1
11257 CYP2A6 19_28 0.9757 32.76 9.303e-05 5.407 1
9054 SPTY2D1 11_13 0.8656 33.81 8.518e-05 -5.557 1Genes with largest z scores
#genes with 20 largest z scores
head(ctwas_gene_res[order(-abs(ctwas_gene_res$z)),report_cols],20) genename region_tag susie_pip mu2 PVE z num_eqtl
4433 PSRC1 1_67 1.000000 1676.75 4.880e-03 -41.687 1
11327 HPR 16_38 1.000000 452.14 1.316e-03 -16.590 1
4315 ANGPTL3 1_39 0.996428 251.54 7.294e-04 16.132 1
NA.365 <NA> 1_121 0.999665 204.92 5.962e-04 -15.108 1
NA.159 <NA> 8_83 0.004677 243.37 3.313e-06 14.404 1
5988 FADS1 11_34 0.995191 156.60 4.536e-04 12.587 1
2454 ST3GAL4 11_77 0.950820 82.25 2.276e-04 11.943 1
8523 TNKS 8_12 0.995525 77.42 2.243e-04 10.918 1
9718 CEACAM19 19_31 0.000000 99.39 0.000e+00 -10.909 1
2092 SP4 7_19 0.980670 103.07 2.941e-04 10.693 1
9910 RHCE 1_18 0.415254 101.60 1.228e-04 10.264 1
9428 TMEM50A 1_18 0.081259 98.23 2.323e-05 10.082 1
9251 ZNF329 19_39 0.969485 107.38 3.030e-04 10.059 1
2309 KPNB1 17_27 0.338600 98.00 9.656e-05 -9.909 1
9438 EMILIN3 20_25 0.025404 93.34 6.901e-06 9.502 1
6615 TMED4 7_32 0.880091 55.44 1.420e-04 9.455 1
6090 CSNK1G3 5_75 0.980012 84.95 2.423e-04 9.116 1
9365 GAS6 13_62 0.990760 71.37 2.058e-04 -8.924 1
11016 APOC2 19_31 0.000000 53.52 0.000e+00 -8.870 1
11372 APOC4 19_31 0.000000 51.50 0.000e+00 8.735 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)
#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)
#number of significant z scores
sum(abs(ctwas_gene_res$z) > sig_thresh)[1] 101#proportion of significant z scores
mean(abs(ctwas_gene_res$z) > sig_thresh)[1] 0.03197#genes with most significant z scores
head(ctwas_gene_res[order(-abs(ctwas_gene_res$z)),report_cols],20) genename region_tag susie_pip mu2 PVE z num_eqtl
4433 PSRC1 1_67 1.000000 1676.75 4.880e-03 -41.687 1
11327 HPR 16_38 1.000000 452.14 1.316e-03 -16.590 1
4315 ANGPTL3 1_39 0.996428 251.54 7.294e-04 16.132 1
NA.365 <NA> 1_121 0.999665 204.92 5.962e-04 -15.108 1
NA.159 <NA> 8_83 0.004677 243.37 3.313e-06 14.404 1
5988 FADS1 11_34 0.995191 156.60 4.536e-04 12.587 1
2454 ST3GAL4 11_77 0.950820 82.25 2.276e-04 11.943 1
8523 TNKS 8_12 0.995525 77.42 2.243e-04 10.918 1
9718 CEACAM19 19_31 0.000000 99.39 0.000e+00 -10.909 1
2092 SP4 7_19 0.980670 103.07 2.941e-04 10.693 1
9910 RHCE 1_18 0.415254 101.60 1.228e-04 10.264 1
9428 TMEM50A 1_18 0.081259 98.23 2.323e-05 10.082 1
9251 ZNF329 19_39 0.969485 107.38 3.030e-04 10.059 1
2309 KPNB1 17_27 0.338600 98.00 9.656e-05 -9.909 1
9438 EMILIN3 20_25 0.025404 93.34 6.901e-06 9.502 1
6615 TMED4 7_32 0.880091 55.44 1.420e-04 9.455 1
6090 CSNK1G3 5_75 0.980012 84.95 2.423e-04 9.116 1
9365 GAS6 13_62 0.990760 71.37 2.058e-04 -8.924 1
11016 APOC2 19_31 0.000000 53.52 0.000e+00 -8.870 1
11372 APOC4 19_31 0.000000 51.50 0.000e+00 8.735 1SNPs with highest PIPs
#snps with PIP>0.8 or 20 highest PIPs
head(ctwas_snp_res[order(-ctwas_snp_res$susie_pip),report_cols_snps],
max(sum(ctwas_snp_res$susie_pip>0.8), 20)) id region_tag susie_pip mu2 PVE z
14831 rs2495502 1_34 1.0000 300.73 8.752e-04 6.2922
68843 rs1042034 2_13 1.0000 237.63 6.915e-04 16.5730
68849 rs934197 2_13 1.0000 414.98 1.208e-03 33.0609
70579 rs780093 2_16 1.0000 167.21 4.866e-04 -14.1426
368612 rs12208357 6_103 1.0000 244.15 7.105e-04 12.2823
368715 rs60425481 6_104 1.0000 34617.58 1.007e-01 -7.1125
761755 rs113408695 17_39 1.0000 146.62 4.267e-04 12.7688
795613 rs73013176 19_9 1.0000 240.92 7.011e-04 -16.2327
805450 rs62117204 19_31 1.0000 825.83 2.403e-03 -44.6722
805468 rs111794050 19_31 1.0000 771.38 2.245e-03 -33.5996
805501 rs814573 19_31 1.0000 2231.68 6.495e-03 55.5379
805503 rs113345881 19_31 1.0000 781.13 2.273e-03 -34.3186
805506 rs12721109 19_31 1.0000 1355.57 3.945e-03 -46.3258
798144 rs3794991 19_15 1.0000 435.64 1.268e-03 -21.4921
761781 rs8070232 17_39 1.0000 152.14 4.428e-04 -8.0915
816677 rs34507316 20_13 1.0000 80.71 2.349e-04 -6.8147
68794 rs11679386 2_12 1.0000 132.05 3.843e-04 11.9094
68929 rs1848922 2_13 1.0000 231.66 6.742e-04 25.4123
68852 rs548145 2_13 1.0000 664.99 1.935e-03 33.0860
496315 rs2437818 9_53 1.0000 69.92 2.035e-04 6.3340
1015362 rs1800961 20_28 1.0000 72.56 2.112e-04 -8.8970
504532 rs115478735 9_70 1.0000 307.40 8.946e-04 19.0118
805841 rs150262789 19_32 1.0000 77.88 2.266e-04 -10.8985
760839 rs1801689 17_38 1.0000 80.97 2.356e-04 9.3964
805164 rs73036721 19_30 1.0000 58.65 1.707e-04 -7.7879
443063 rs4738679 8_45 1.0000 108.15 3.147e-04 -11.6999
274809 rs1499279 5_30 1.0000 62.03 1.805e-04 -8.3746
76644 rs72800939 2_28 1.0000 55.98 1.629e-04 -7.8457
795651 rs137992968 19_9 1.0000 114.51 3.333e-04 -10.7526
14842 rs10888896 1_34 1.0000 134.32 3.909e-04 11.8938
7646 rs79598313 1_18 1.0000 46.89 1.365e-04 7.0246
462724 rs13252684 8_83 1.0000 227.38 6.617e-04 11.9644
441668 rs140753685 8_42 1.0000 55.16 1.605e-04 7.7992
805209 rs62115478 19_30 1.0000 183.16 5.330e-04 -14.3262
52998 rs2807848 1_112 1.0000 54.88 1.597e-04 -7.8828
14801 rs11580527 1_34 1.0000 88.52 2.576e-04 -11.1672
14849 rs471705 1_34 1.0000 210.38 6.122e-04 16.2630
350049 rs9496567 6_67 1.0000 38.86 1.131e-04 -6.3402
319854 rs11376017 6_13 0.9999 65.40 1.903e-04 -8.5079
795677 rs4804149 19_10 0.9999 46.15 1.343e-04 6.5194
816676 rs6075251 20_13 0.9998 53.98 1.571e-04 -2.3298
798175 rs113619686 19_15 0.9998 56.13 1.633e-04 0.5939
76508 rs139029940 2_27 0.9997 39.11 1.138e-04 6.8150
703812 rs2070895 15_26 0.9996 58.63 1.706e-04 7.7347
368803 rs374071816 6_104 0.9996 6415.76 1.866e-02 16.2541
795642 rs1569372 19_9 0.9993 278.34 8.095e-04 10.0055
542886 rs17875416 10_71 0.9993 37.72 1.097e-04 -6.2663
795637 rs3745677 19_9 0.9993 90.85 2.642e-04 9.3358
795730 rs322144 19_10 0.9992 56.74 1.650e-04 3.9466
323940 rs454182 6_22 0.9992 35.39 1.029e-04 4.7791
609330 rs7397189 12_36 0.9991 34.12 9.920e-05 -5.7710
496288 rs2297400 9_53 0.9989 40.92 1.190e-04 6.6057
795634 rs147985405 19_9 0.9986 2286.17 6.644e-03 -48.9352
281261 rs7701166 5_44 0.9986 33.45 9.719e-05 -2.4848
797784 rs2302209 19_14 0.9981 42.79 1.243e-04 6.6360
431395 rs1495743 8_20 0.9978 40.73 1.183e-04 -6.5160
740565 rs2255451 16_48 0.9959 38.08 1.104e-04 -6.3628
585721 rs3135506 11_70 0.9956 147.38 4.270e-04 12.3730
443031 rs56386732 8_45 0.9955 34.46 9.983e-05 -7.0123
585726 rs75542613 11_70 0.9954 35.61 1.032e-04 -6.5344
821630 rs76981217 20_24 0.9953 35.23 1.020e-04 7.6925
324377 rs3130253 6_23 0.9942 29.66 8.583e-05 5.6415
613696 rs148481241 12_44 0.9929 27.35 7.902e-05 5.0955
625914 rs653178 12_67 0.9924 92.80 2.680e-04 11.0501
281202 rs10062361 5_44 0.9869 202.05 5.803e-04 20.3206
806761 rs838145 19_33 0.9856 97.91 2.809e-04 -11.8738
735238 rs4396539 16_37 0.9854 27.36 7.847e-05 -5.2329
137892 rs709149 3_9 0.9851 35.61 1.021e-04 -6.7820
325162 rs28780090 6_24 0.9829 49.14 1.406e-04 6.8714
404191 rs3197597 7_61 0.9818 29.19 8.339e-05 -5.0452
630003 rs11057830 12_76 0.9809 25.68 7.330e-05 4.9296
325185 rs62407548 6_24 0.9802 63.62 1.815e-04 8.2573
144902 rs9834932 3_24 0.9801 65.63 1.872e-04 -8.4816
821581 rs6029132 20_24 0.9795 39.13 1.115e-04 -6.7625
821634 rs73124945 20_24 0.9793 32.10 9.150e-05 -7.7754
388423 rs141379002 7_33 0.9720 25.45 7.200e-05 4.8970
470776 rs7024888 9_3 0.9695 25.42 7.173e-05 -5.0558
462713 rs79658059 8_83 0.9690 269.87 7.611e-04 -16.0220
244616 rs114756490 4_100 0.9690 26.06 7.349e-05 4.9889
805824 rs34942359 19_32 0.9676 62.00 1.746e-04 -7.0096
829635 rs62219001 21_2 0.9626 25.96 7.273e-05 -4.9484
221887 rs1458038 4_54 0.9600 52.32 1.462e-04 -7.4179
478640 rs1556516 9_16 0.9557 72.76 2.024e-04 -8.9921
594353 rs11048034 12_9 0.9540 35.50 9.856e-05 6.1337
764914 rs4969183 17_44 0.9522 48.50 1.344e-04 7.1693
628868 rs1169300 12_74 0.9474 67.72 1.867e-04 8.6855
323401 rs75080831 6_19 0.9439 56.44 1.550e-04 -7.9067
624007 rs1196760 12_63 0.9412 25.69 7.036e-05 -4.8667
324348 rs28986304 6_23 0.9319 41.73 1.132e-04 7.3825
76524 rs4076834 2_27 0.9314 425.49 1.153e-03 -20.1086
352785 rs12199109 6_73 0.9272 24.50 6.609e-05 4.8570
569350 rs6591179 11_36 0.9265 24.78 6.683e-05 4.8933
193512 rs5855544 3_120 0.9264 23.69 6.387e-05 -4.5937
76521 rs13430143 2_27 0.9231 76.76 2.062e-04 -3.3445
68846 rs78610189 2_13 0.9181 59.17 1.581e-04 -8.3855
368606 rs9456502 6_103 0.9140 33.08 8.798e-05 5.9640
427072 rs117037226 8_11 0.9072 23.62 6.237e-05 4.1922
805741 rs377297589 19_32 0.9063 50.46 1.331e-04 -6.7865
14832 rs1887552 1_34 0.9063 344.07 9.075e-04 -9.8686
751298 rs117859452 17_17 0.9031 24.14 6.345e-05 -3.8517
836876 rs2835302 21_16 0.9017 25.15 6.598e-05 -4.6537
703811 rs139823028 15_26 0.8994 23.59 6.175e-05 3.9898
195299 rs36205397 4_4 0.8993 38.35 1.004e-04 6.1594
169895 rs189174 3_74 0.8954 43.56 1.135e-04 6.7678
731346 rs821840 16_30 0.8951 163.02 4.247e-04 -13.4753
509482 rs10905277 10_8 0.8941 27.80 7.234e-05 5.1258
812322 rs74273659 20_5 0.8931 24.47 6.360e-05 4.6468
197524 rs2002574 4_10 0.8920 24.29 6.304e-05 -4.5583
542597 rs12244851 10_70 0.8902 36.36 9.420e-05 -4.8831
795718 rs322125 19_10 0.8873 101.66 2.625e-04 -7.4704
751207 rs3032928 17_17 0.8835 33.72 8.669e-05 6.1119
496308 rs2777788 9_53 0.8783 57.78 1.477e-04 -5.7370
581990 rs201912654 11_59 0.8714 39.91 1.012e-04 -6.3056
825133 rs10641149 20_32 0.8687 26.93 6.807e-05 5.0758
638890 rs1012130 13_10 0.8681 38.76 9.792e-05 -2.7810
848964 rs145678077 22_17 0.8565 24.69 6.154e-05 -4.8686
119989 rs7569317 2_120 0.8546 44.04 1.095e-04 7.9007
68646 rs6531234 2_12 0.8543 42.09 1.046e-04 -7.1708
795687 rs58495388 19_10 0.8501 33.71 8.338e-05 5.5313
486626 rs11144506 9_35 0.8486 26.90 6.644e-05 5.0427
358988 rs9321207 6_86 0.8475 30.33 7.481e-05 5.4016
821599 rs6102034 20_24 0.8443 96.35 2.367e-04 -11.1900
281225 rs3843482 5_44 0.8372 395.85 9.645e-04 25.0344
820375 rs11167269 20_21 0.8326 56.80 1.376e-04 -7.7950
756426 rs4793601 17_28 0.8268 30.55 7.352e-05 -6.2095
816657 rs78348000 20_13 0.8209 30.02 7.171e-05 5.2206
536776 rs10882161 10_59 0.8165 29.78 7.076e-05 -5.4756
761766 rs9303012 17_39 0.8164 144.47 3.432e-04 2.2591
638882 rs1799955 13_10 0.8149 69.86 1.657e-04 -6.6936
793033 rs12459030 19_4 0.8133 24.48 5.794e-05 -4.3721
722803 rs35782593 16_12 0.8132 24.15 5.716e-05 -4.3189SNPs 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 susie_pip mu2 PVE z
368711 rs3106169 6_104 6.210e-01 34666 6.265e-02 11.139
368712 rs3127598 6_104 4.710e-01 34665 4.752e-02 11.135
368720 rs3106167 6_104 4.787e-01 34665 4.829e-02 11.136
368704 rs11755965 6_104 1.257e-01 34655 1.268e-02 11.140
368715 rs60425481 6_104 1.000e+00 34618 1.007e-01 -7.113
368695 rs12194962 6_104 4.484e-07 34582 4.512e-08 11.106
368713 rs3127597 6_104 7.406e-08 34560 7.448e-09 11.145
368674 rs3119311 6_104 0.000e+00 25050 0.000e+00 8.031
368668 rs3127579 6_104 0.000e+00 18252 0.000e+00 7.568
368662 rs10945658 6_104 0.000e+00 15988 0.000e+00 8.309
368657 rs3103352 6_104 0.000e+00 15952 0.000e+00 8.522
368661 rs3119308 6_104 0.000e+00 15949 0.000e+00 8.274
368653 rs3101821 6_104 0.000e+00 15896 0.000e+00 8.528
368659 rs12205178 6_104 0.000e+00 15859 0.000e+00 8.297
368651 rs148015788 6_104 0.000e+00 15660 0.000e+00 8.351
368762 rs3124784 6_104 0.000e+00 13154 0.000e+00 9.680
368763 rs3127596 6_104 0.000e+00 11943 0.000e+00 9.556
368756 rs3127599 6_104 0.000e+00 11880 0.000e+00 9.259
368726 rs2481030 6_104 0.000e+00 11348 0.000e+00 4.811
368691 rs2504949 6_104 0.000e+00 9336 0.000e+00 2.937
368744 rs388170 6_104 0.000e+00 8646 0.000e+00 3.833
368666 rs316013 6_104 0.000e+00 8286 0.000e+00 -3.002
368667 rs316012 6_104 0.000e+00 8187 0.000e+00 -3.074
368747 rs9355288 6_104 0.000e+00 8030 0.000e+00 6.319
368655 rs610206 6_104 0.000e+00 7566 0.000e+00 -2.944
368656 rs595374 6_104 0.000e+00 7551 0.000e+00 -2.921
368663 rs315995 6_104 0.000e+00 7369 0.000e+00 -3.207
368660 rs543435 6_104 0.000e+00 7342 0.000e+00 -3.250
368709 rs452867 6_104 0.000e+00 6963 0.000e+00 -7.124
368718 rs367334 6_104 0.000e+00 6958 0.000e+00 -7.106
368706 rs589931 6_104 0.000e+00 6957 0.000e+00 -7.116
368707 rs600584 6_104 0.000e+00 6957 0.000e+00 -7.113
368708 rs434953 6_104 0.000e+00 6957 0.000e+00 -7.111
368714 rs380498 6_104 0.000e+00 6957 0.000e+00 -7.115
368682 rs3119312 6_104 0.000e+00 6639 0.000e+00 3.771
368803 rs374071816 6_104 9.996e-01 6416 1.866e-02 16.254
368741 rs2872317 6_104 0.000e+00 6123 0.000e+00 6.746
368738 rs2313453 6_104 0.000e+00 6118 0.000e+00 6.718
368808 rs4252185 6_104 4.487e-04 5922 7.732e-06 15.878
368729 rs146184004 6_104 0.000e+00 5824 0.000e+00 6.534
368732 rs624319 6_104 0.000e+00 5759 0.000e+00 -6.291
368731 rs637614 6_104 0.000e+00 5752 0.000e+00 -6.362
368733 rs486339 6_104 0.000e+00 5712 0.000e+00 -6.311
368678 rs316036 6_104 0.000e+00 5610 0.000e+00 -7.009
368730 rs555754 6_104 0.000e+00 5572 0.000e+00 -6.593
368809 rs12212146 6_104 0.000e+00 4422 0.000e+00 -2.410
368676 rs582280 6_104 0.000e+00 4291 0.000e+00 2.635
368675 rs497039 6_104 0.000e+00 4290 0.000e+00 2.634
368759 rs9346818 6_104 0.000e+00 3538 0.000e+00 7.950
368862 rs1247539 6_104 0.000e+00 3483 0.000e+00 -4.294SNPs with highest PVE
#SNPs with 50 highest pve
head(ctwas_snp_res[order(-ctwas_snp_res$PVE),report_cols_snps],50) id region_tag susie_pip mu2 PVE z
368715 rs60425481 6_104 1.0000 34617.58 0.1007435 -7.113
368711 rs3106169 6_104 0.6210 34665.56 0.0626470 11.139
368720 rs3106167 6_104 0.4787 34665.13 0.0482930 11.136
368712 rs3127598 6_104 0.4710 34665.21 0.0475157 11.135
368803 rs374071816 6_104 0.9996 6415.76 0.0186626 16.254
368704 rs11755965 6_104 0.1257 34655.20 0.0126789 11.140
795634 rs147985405 19_9 0.9986 2286.17 0.0066440 -48.935
805501 rs814573 19_31 1.0000 2231.68 0.0064946 55.538
805506 rs12721109 19_31 1.0000 1355.57 0.0039450 -46.326
805450 rs62117204 19_31 1.0000 825.83 0.0024033 -44.672
805503 rs113345881 19_31 1.0000 781.13 0.0022732 -34.319
805468 rs111794050 19_31 1.0000 771.38 0.0022448 -33.600
68852 rs548145 2_13 1.0000 664.99 0.0019352 33.086
798144 rs3794991 19_15 1.0000 435.64 0.0012678 -21.492
68849 rs934197 2_13 1.0000 414.98 0.0012077 33.061
76524 rs4076834 2_27 0.9314 425.49 0.0011533 -20.109
281225 rs3843482 5_44 0.8372 395.85 0.0009645 25.034
14832 rs1887552 1_34 0.9063 344.07 0.0009075 -9.869
504532 rs115478735 9_70 1.0000 307.40 0.0008946 19.012
14831 rs2495502 1_34 1.0000 300.73 0.0008752 6.292
795642 rs1569372 19_9 0.9993 278.34 0.0008095 10.006
462713 rs79658059 8_83 0.9690 269.87 0.0007611 -16.022
368612 rs12208357 6_103 1.0000 244.15 0.0007105 12.282
795613 rs73013176 19_9 1.0000 240.92 0.0007011 -16.233
68843 rs1042034 2_13 1.0000 237.63 0.0006915 16.573
68929 rs1848922 2_13 1.0000 231.66 0.0006742 25.412
462724 rs13252684 8_83 1.0000 227.38 0.0006617 11.964
14849 rs471705 1_34 1.0000 210.38 0.0006122 16.263
281202 rs10062361 5_44 0.9869 202.05 0.0005803 20.321
805209 rs62115478 19_30 1.0000 183.16 0.0005330 -14.326
70579 rs780093 2_16 1.0000 167.21 0.0004866 -14.143
761781 rs8070232 17_39 1.0000 152.14 0.0004428 -8.091
368626 rs3818678 6_103 0.7665 197.23 0.0004399 -9.948
585721 rs3135506 11_70 0.9956 147.38 0.0004270 12.373
761755 rs113408695 17_39 1.0000 146.62 0.0004267 12.769
731346 rs821840 16_30 0.8951 163.02 0.0004247 -13.475
14842 rs10888896 1_34 1.0000 134.32 0.0003909 11.894
68794 rs11679386 2_12 1.0000 132.05 0.0003843 11.909
761766 rs9303012 17_39 0.8164 144.47 0.0003432 2.259
306104 rs12657266 5_92 0.7522 156.65 0.0003429 13.895
795651 rs137992968 19_9 1.0000 114.51 0.0003333 -10.753
443063 rs4738679 8_45 1.0000 108.15 0.0003147 -11.700
462712 rs2980875 8_83 0.5510 184.92 0.0002965 -22.102
806761 rs838145 19_33 0.9856 97.91 0.0002809 -11.874
625914 rs653178 12_67 0.9924 92.80 0.0002680 11.050
795637 rs3745677 19_9 0.9993 90.85 0.0002642 9.336
795718 rs322125 19_10 0.8873 101.66 0.0002625 -7.470
14801 rs11580527 1_34 1.0000 88.52 0.0002576 -11.167
821775 rs11086801 20_25 0.7818 106.07 0.0002413 10.975
821599 rs6102034 20_24 0.8443 96.35 0.0002367 -11.190SNPs with largest z scores
#histogram of (abs) SNP z scores
hist(abs(ctwas_snp_res$z))
#SNPs with 50 largest z scores
head(ctwas_snp_res[order(-abs(ctwas_snp_res$z)),report_cols_snps],50) id region_tag susie_pip mu2 PVE z
805501 rs814573 19_31 1.000e+00 2231.7 6.495e-03 55.54
795634 rs147985405 19_9 9.986e-01 2286.2 6.644e-03 -48.94
795629 rs73015020 19_9 8.132e-04 2273.9 5.381e-06 -48.80
795627 rs138175288 19_9 3.800e-04 2272.1 2.513e-06 -48.78
795628 rs138294113 19_9 9.208e-05 2268.2 6.078e-07 -48.75
795630 rs77140532 19_9 5.573e-05 2268.7 3.680e-07 -48.74
795631 rs112552009 19_9 2.794e-05 2264.7 1.841e-07 -48.71
795632 rs10412048 19_9 1.129e-05 2265.4 7.443e-08 -48.70
795626 rs55997232 19_9 2.986e-09 2245.0 1.951e-11 -48.52
805506 rs12721109 19_31 1.000e+00 1355.6 3.945e-03 -46.33
805450 rs62117204 19_31 1.000e+00 825.8 2.403e-03 -44.67
805437 rs1551891 19_31 0.000e+00 500.6 0.000e+00 -42.27
875656 rs12740374 1_67 5.982e-04 1473.3 2.565e-06 -41.79
875652 rs7528419 1_67 6.014e-04 1469.3 2.572e-06 -41.74
875663 rs646776 1_67 5.262e-04 1468.1 2.248e-06 41.73
875662 rs629301 1_67 4.946e-04 1464.4 2.108e-06 41.69
875674 rs583104 1_67 5.301e-04 1423.3 2.196e-06 41.09
875677 rs4970836 1_67 5.222e-04 1420.3 2.158e-06 41.05
875679 rs1277930 1_67 5.314e-04 1415.6 2.189e-06 40.98
875680 rs599839 1_67 5.444e-04 1414.6 2.241e-06 40.96
795635 rs17248769 19_9 1.328e-07 1721.5 6.655e-10 -40.84
795636 rs2228671 19_9 9.375e-08 1710.4 4.666e-10 -40.70
875660 rs3832016 1_67 4.039e-04 1375.1 1.616e-06 40.40
875657 rs660240 1_67 4.032e-04 1367.8 1.605e-06 40.29
875675 rs602633 1_67 4.386e-04 1346.1 1.718e-06 39.96
795625 rs9305020 19_9 3.120e-14 1305.6 1.185e-16 -34.84
805497 rs405509 19_31 0.000e+00 976.1 0.000e+00 -34.64
875643 rs4970834 1_67 7.888e-04 1014.8 2.329e-06 -34.62
805503 rs113345881 19_31 1.000e+00 781.1 2.273e-03 -34.32
805421 rs62120566 19_31 0.000e+00 1335.0 0.000e+00 -33.74
805468 rs111794050 19_31 1.000e+00 771.4 2.245e-03 -33.60
68852 rs548145 2_13 1.000e+00 665.0 1.935e-03 33.09
805474 rs4802238 19_31 0.000e+00 979.3 0.000e+00 33.08
68849 rs934197 2_13 1.000e+00 415.0 1.208e-03 33.06
805415 rs188099946 19_31 0.000e+00 1279.7 0.000e+00 -33.04
805485 rs2972559 19_31 0.000e+00 1308.1 0.000e+00 32.29
805409 rs201314191 19_31 0.000e+00 1186.6 0.000e+00 -32.07
875664 rs3902354 1_67 4.510e-04 866.7 1.138e-06 32.00
875653 rs11102967 1_67 4.528e-04 863.2 1.137e-06 31.94
875678 rs4970837 1_67 5.075e-04 859.4 1.269e-06 31.86
805476 rs56394238 19_31 0.000e+00 972.3 0.000e+00 31.55
805453 rs2965169 19_31 0.000e+00 361.2 0.000e+00 -31.38
805477 rs3021439 19_31 0.000e+00 865.7 0.000e+00 31.05
875648 rs611917 1_67 4.313e-04 812.6 1.020e-06 -30.98
68879 rs12997242 2_13 2.825e-11 382.6 3.145e-14 30.82
805484 rs12162222 19_31 0.000e+00 1120.2 0.000e+00 30.50
68853 rs478588 2_13 8.642e-11 612.9 1.541e-13 30.49
805414 rs62119327 19_31 0.000e+00 1044.9 0.000e+00 -30.42
68854 rs56350433 2_13 3.662e-12 350.9 3.740e-15 30.23
68859 rs56079819 2_13 3.669e-12 350.1 3.738e-15 30.19
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