Last updated: 2023-01-23

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Rmd 4d68754 sq-96 2023-01-23 update
html 4d68754 sq-96 2023-01-23 update

Weight QC

[1] 11502
[1] 3347

  1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18  19  20 
324 225 166 135 135 217 173 111 134 134 210 187  61 100 109 185 195  46 258  94 
 21  22 
 48 100 
[1] 1

Load 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 
0.000144 0.035782 
#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 
13.96 15.68 
#estimated enrichment
estimated_enrichment <- estimated_enrichment_all[ncol(group_prior_var_rec)]
print(estimated_enrichment)
[1] 248.4
#report sample size
print(sample_size)
[1] 343621
#report group size
print(group_size)
    SNP    gene 
8696600    3347 
#estimated group PVE
estimated_group_pve <- estimated_group_pve_all[,ncol(group_prior_rec)]
print(estimated_group_pve)
     SNP     gene 
0.050907 0.005465 
#total PVE
sum(estimated_group_pve)
[1] 0.05637
#attributable PVE
estimated_group_pve/sum(estimated_group_pve)
    SNP    gene 
0.90305 0.09695 

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 823.87 2.398e-03 -41.793        1
9251     ZNF329      19_39    0.9942 106.53 3.082e-04  10.436        1
10708    NYNRIN       14_3    0.9921  53.33 1.540e-04   7.679        1
1597       PLTP      20_28    0.9921  56.81 1.640e-04  -5.732        1
NA.396     <NA>       8_12    0.9902  77.05 2.220e-04  10.465        1
11257    CYP2A6      19_28    0.9891  30.54 8.790e-05   5.407        1
9365       GAS6      13_62    0.9873  65.49 1.882e-04  -8.924        1
6774       PKN3       9_66    0.9859  45.73 1.312e-04  -6.621        1
5988      FADS1      11_34    0.9711 145.75 4.119e-04  12.675        1
NA.392     <NA>      1_121    0.9682 189.43 5.337e-04 -15.074        1
9046    KLHDC7A       1_13    0.9634  19.65 5.510e-05   4.124        1
9054    SPTY2D1      11_13    0.9459  31.38 8.637e-05  -5.587        1
1309       FMO2       1_84    0.9347  25.01 6.802e-05   4.838        1
2092        SP4       7_19    0.9196  93.93 2.514e-04  10.701        1
9827      PALM3      19_11    0.9143  18.64 4.960e-05   3.839        1
2454    ST3GAL4      11_77    0.9113  73.45 1.948e-04  11.734        1
6855   ALDH16A1      19_34    0.9009  27.97 7.334e-05  -4.119        1
10459     PRMT6       1_66    0.9008  30.36 7.958e-05  -5.374        1
8418       GNB2       7_62    0.9002  27.56 7.220e-05   5.813        1
1320    CWF19L1      10_64    0.8948  32.86 8.558e-05   5.707        1
7350       BRI3       7_60    0.8845  26.39 6.793e-05  -5.067        1
697        PIGB      15_24    0.8805  17.59 4.507e-05   3.665        1
7918       PDHB       3_40    0.8665  25.15 6.342e-05   3.304        1
3714   SLC2A4RG      20_38    0.8626  30.41 7.635e-05  -5.563        1
3659       GNMT       6_33    0.8575  26.56 6.628e-05   5.058        1
7542       LIPC      15_26    0.8485  63.23 1.561e-04  -7.731        1
1114       SRRT       7_62    0.8396  28.50 6.963e-05   5.938        1
10429       PNP       14_1    0.8284  17.49 4.216e-05  -3.575        1
NA.395     <NA>       5_78    0.8280  17.74 4.276e-05  -3.817        1
4669      SCYL2      12_59    0.8229  17.54 4.200e-05  -3.564        1
7092      NEK10       3_20    0.8183  21.58 5.140e-05  -4.089        1

Genes 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
10399       LPA      6_104 0.000e+00 13352.87 0.000e+00   6.319        1
5797    SLC22A3      6_104 0.000e+00  9690.02 0.000e+00  -6.225        1
4433      PSRC1       1_67 1.000e+00   823.87 2.398e-03 -41.793        1
NA.139     <NA>      6_104 0.000e+00   430.46 0.000e+00  -8.475        1
3270    ALDH6A1      14_34 2.732e-01   263.13 2.092e-04   4.361        1
5166      PTGR2      14_34 4.395e-04   256.75 3.284e-07  -3.091        1
5375     GEMIN7      19_31 0.000e+00   251.13 0.000e+00  14.336        1
8026      PCSK9       1_34 9.971e-05   238.01 6.907e-08  16.079        1
4315    ANGPTL3       1_39 9.475e-02   204.00 5.625e-05  15.169        1
NA.392     <NA>      1_121 9.682e-01   189.43 5.337e-04 -15.074        1
NA.397     <NA>       8_83 1.112e-01   164.21 5.314e-05  17.282        1
8700        ABO       9_70 7.330e-02   149.53 3.190e-05  12.100        1
10549   HLA-DMA       6_27 5.937e-03   145.77 2.518e-06  -2.364        1
5988      FADS1      11_34 9.711e-01   145.75 4.119e-04  12.675        1
2077    ATP13A1      19_15 5.775e-01   134.05 2.253e-04 -13.541        1
10926     FADS3      11_34 2.877e-02   111.20 9.310e-06  11.074        1
9251     ZNF329      19_39 9.942e-01   106.53 3.082e-04  10.436        1
2092        SP4       7_19 9.196e-01    93.93 2.514e-04  10.701        1
9025    EFCAB13      17_27 3.299e-01    92.58 8.889e-05  10.027        1
4047    NECTIN2      19_31 0.000e+00    91.26 0.000e+00   5.825        1

Genes 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 823.87 2.398e-03 -41.793        1
NA.392     <NA>      1_121    0.9682 189.43 5.337e-04 -15.074        1
5988      FADS1      11_34    0.9711 145.75 4.119e-04  12.675        1
9251     ZNF329      19_39    0.9942 106.53 3.082e-04  10.436        1
2092        SP4       7_19    0.9196  93.93 2.514e-04  10.701        1
2077    ATP13A1      19_15    0.5775 134.05 2.253e-04 -13.541        1
NA.396     <NA>       8_12    0.9902  77.05 2.220e-04  10.465        1
3270    ALDH6A1      14_34    0.2732 263.13 2.092e-04   4.361        1
2454    ST3GAL4      11_77    0.9113  73.45 1.948e-04  11.734        1
9365       GAS6      13_62    0.9873  65.49 1.882e-04  -8.924        1
6090    CSNK1G3       5_75    0.7883  72.62 1.666e-04   8.881        1
1597       PLTP      20_28    0.9921  56.81 1.640e-04  -5.732        1
7542       LIPC      15_26    0.8485  63.23 1.561e-04  -7.731        1
10708    NYNRIN       14_3    0.9921  53.33 1.540e-04   7.679        1
6774       PKN3       9_66    0.9859  45.73 1.312e-04  -6.621        1
9025    EFCAB13      17_27    0.3299  92.58 8.889e-05  10.027        1
11257    CYP2A6      19_28    0.9891  30.54 8.790e-05   5.407        1
9054    SPTY2D1      11_13    0.9459  31.38 8.637e-05  -5.587        1
1320    CWF19L1      10_64    0.8948  32.86 8.558e-05   5.707        1
10459     PRMT6       1_66    0.9008  30.36 7.958e-05  -5.374        1

Genes 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 1.000e+00 823.87 2.398e-03 -41.79        1
NA.397     <NA>       8_83 1.112e-01 164.21 5.314e-05  17.28        1
8026      PCSK9       1_34 9.971e-05 238.01 6.907e-08  16.08        1
4315    ANGPTL3       1_39 9.475e-02 204.00 5.625e-05  15.17        1
NA.392     <NA>      1_121 9.682e-01 189.43 5.337e-04 -15.07        1
5375     GEMIN7      19_31 0.000e+00 251.13 0.000e+00  14.34        1
2077    ATP13A1      19_15 5.775e-01 134.05 2.253e-04 -13.54        1
5988      FADS1      11_34 9.711e-01 145.75 4.119e-04  12.67        1
11016     APOC2      19_31 0.000e+00  88.82 0.000e+00 -12.21        1
8700        ABO       9_70 7.330e-02 149.53 3.190e-05  12.10        1
2454    ST3GAL4      11_77 9.113e-01  73.45 1.948e-04  11.73        1
10926     FADS3      11_34 2.877e-02 111.20 9.310e-06  11.07        1
6183       POC5       5_44 1.441e-02  75.86 3.181e-06  10.86        1
2092        SP4       7_19 9.196e-01  93.93 2.514e-04  10.70        1
NA.396     <NA>       8_12 9.902e-01  77.05 2.220e-04  10.46        1
9251     ZNF329      19_39 9.942e-01 106.53 3.082e-04  10.44        1
2094     DNAH11       7_19 5.080e-02  88.49 1.308e-05  10.23        1
8523       TNKS       8_12 1.744e-01  66.86 3.394e-05  10.13        1
9025    EFCAB13      17_27 3.299e-01  92.58 8.889e-05  10.03        1
9910       RHCE       1_18 7.008e-02  89.44 1.824e-05  10.02        1

Comparing 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$z) > sig_thresh)
[1] 113
#proportion of significant z scores
mean(abs(ctwas_gene_res$z) > sig_thresh)
[1] 0.03376
#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 1.000e+00 823.87 2.398e-03 -41.79        1
NA.397     <NA>       8_83 1.112e-01 164.21 5.314e-05  17.28        1
8026      PCSK9       1_34 9.971e-05 238.01 6.907e-08  16.08        1
4315    ANGPTL3       1_39 9.475e-02 204.00 5.625e-05  15.17        1
NA.392     <NA>      1_121 9.682e-01 189.43 5.337e-04 -15.07        1
5375     GEMIN7      19_31 0.000e+00 251.13 0.000e+00  14.34        1
2077    ATP13A1      19_15 5.775e-01 134.05 2.253e-04 -13.54        1
5988      FADS1      11_34 9.711e-01 145.75 4.119e-04  12.67        1
11016     APOC2      19_31 0.000e+00  88.82 0.000e+00 -12.21        1
8700        ABO       9_70 7.330e-02 149.53 3.190e-05  12.10        1
2454    ST3GAL4      11_77 9.113e-01  73.45 1.948e-04  11.73        1
10926     FADS3      11_34 2.877e-02 111.20 9.310e-06  11.07        1
6183       POC5       5_44 1.441e-02  75.86 3.181e-06  10.86        1
2092        SP4       7_19 9.196e-01  93.93 2.514e-04  10.70        1
NA.396     <NA>       8_12 9.902e-01  77.05 2.220e-04  10.46        1
9251     ZNF329      19_39 9.942e-01 106.53 3.082e-04  10.44        1
2094     DNAH11       7_19 5.080e-02  88.49 1.308e-05  10.23        1
8523       TNKS       8_12 1.744e-01  66.86 3.394e-05  10.13        1
9025    EFCAB13      17_27 3.299e-01  92.58 8.889e-05  10.03        1
9910       RHCE       1_18 7.008e-02  89.44 1.824e-05  10.02        1

SNPs 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
70338     rs1042034       2_13    1.0000   244.90 7.127e-04  16.5730
70344      rs934197       2_13    1.0000   414.29 1.206e-03  33.0609
72074      rs780093       2_16    1.0000   170.40 4.959e-04 -14.1426
324246  rs115740542       6_20    1.0000   164.34 4.783e-04 -12.5323
367370   rs12208357      6_103    1.0000   256.54 7.466e-04  12.2823
367473   rs60425481      6_104    1.0000 56798.34 1.653e-01  -7.1125
677728  rs369107859      14_34    1.0000  1054.21 3.068e-03  -2.2480
756650  rs113408695      17_39    1.0000   151.01 4.395e-04  12.7688
790508   rs73013176       19_9    1.0000   247.13 7.192e-04 -16.2327
800345   rs62117204      19_31    1.0000   826.47 2.405e-03 -44.6722
800363  rs111794050      19_31    1.0000   784.25 2.282e-03 -33.5996
800396     rs814573      19_31    1.0000  2276.75 6.626e-03  55.5379
800398  rs113345881      19_31    1.0000   795.97 2.316e-03 -34.3186
800401   rs12721109      19_31    1.0000  1379.27 4.014e-03 -46.3258
857431   rs11591147       1_34    1.0000  1261.29 3.671e-03 -39.1649
930791   rs67138090       6_27    1.0000   954.13 2.777e-03   4.4111
793039    rs3794991      19_15    1.0000   425.19 1.237e-03 -21.4921
756676    rs8070232      17_39    1.0000   165.98 4.830e-04  -8.0915
961976   rs28601761       8_83    1.0000   343.47 9.996e-04 -25.2552
70289    rs11679386       2_12    1.0000   146.11 4.252e-04  11.9094
70424     rs1848922       2_13    1.0000   234.65 6.829e-04  25.4123
70347      rs548145       2_13    1.0000   679.15 1.976e-03  33.0860
494792    rs2437818       9_53    1.0000    73.44 2.137e-04   6.3340
503009  rs115478735       9_70    1.0000   315.06 9.169e-04  19.0118
1072634   rs1800961      20_28    1.0000    74.44 2.166e-04  -8.8970
800736  rs150262789      19_32    1.0000    78.19 2.276e-04 -10.8985
755734    rs1801689      17_38    1.0000    83.33 2.425e-04   9.3964
800059   rs73036721      19_30    1.0000    60.20 1.752e-04  -7.7879
729965   rs12149380      16_38    1.0000   115.92 3.373e-04  -4.1646
442304    rs4738679       8_45    1.0000   110.81 3.225e-04 -11.6999
275773    rs1499279       5_30    1.0000    64.00 1.862e-04  -8.3746
78139    rs72800939       2_28    1.0000    57.36 1.669e-04  -7.8457
790546  rs137992968       19_9    1.0000   117.64 3.424e-04 -10.7526
387614     rs217396       7_32    1.0000    79.20 2.305e-04  -9.4286
7646     rs79598313       1_18    1.0000    48.08 1.399e-04   7.0246
440909  rs140753685       8_42    1.0000    57.09 1.662e-04   7.7992
800104   rs62115478      19_30    1.0000   188.25 5.478e-04 -14.3262
53653     rs2807848      1_112    1.0000    56.76 1.652e-04  -7.8828
348807    rs9496567       6_67    1.0000    39.84 1.159e-04  -6.3402
324225   rs72834643       6_20    0.9999    46.24 1.346e-04  -6.0487
961992  rs112875651       8_83    0.9999   304.15 8.851e-04 -24.2936
320517   rs11376017       6_13    0.9999    67.28 1.958e-04  -8.5079
790572    rs4804149      19_10    0.9998    47.41 1.379e-04   6.5194
793070  rs113619686      19_15    0.9997    57.28 1.667e-04   0.5939
324979     rs454182       6_22    0.9997    38.89 1.131e-04   4.7791
857494     rs499883       1_34    0.9997   203.10 5.909e-04  16.1075
78003   rs139029940       2_27    0.9997    39.73 1.156e-04   6.8150
367561  rs374071816      6_104    0.9996 10391.13 3.023e-02  16.2541
730008   rs57186116      16_38    0.9995    69.52 2.022e-04   7.7146
790537    rs1569372       19_9    0.9995   294.46 8.565e-04  10.0055
790625     rs322144      19_10    0.9994    60.64 1.764e-04   3.9466
540086   rs17875416      10_71    0.9994    38.89 1.131e-04  -6.2663
606070    rs7397189      12_36    0.9991    34.92 1.015e-04  -5.7710
282225    rs7701166       5_44    0.9991    35.36 1.028e-04  -2.4848
494765    rs2297400       9_53    0.9990    41.87 1.217e-04   6.6057
790529  rs147985405       19_9    0.9988  2357.05 6.851e-03 -48.9352
792679    rs2302209      19_14    0.9984    43.94 1.277e-04   6.6360
430636    rs1495743       8_20    0.9981    41.86 1.216e-04  -6.5160
582921    rs3135506      11_70    0.9960   151.40 4.389e-04  12.3730
582926   rs75542613      11_70    0.9958    36.39 1.054e-04  -6.5344
815140   rs76981217      20_24    0.9956    35.66 1.033e-04   7.6925
442272   rs56386732       8_45    0.9955    35.08 1.016e-04  -7.0123
735460    rs2255451      16_48    0.9948    37.91 1.097e-04  -6.3628
325416    rs3130253       6_23    0.9943    30.54 8.837e-05   5.6415
622062     rs653178      12_67    0.9938    98.63 2.853e-04  11.0501
610436  rs148481241      12_44    0.9911    27.97 8.067e-05   5.0955
282166   rs10062361       5_44    0.9896   210.17 6.053e-04  20.3206
801656     rs838145      19_33    0.9881   101.19 2.910e-04 -11.8738
790532    rs3745677       19_9    0.9881    94.85 2.728e-04   9.3358
140939     rs709149        3_9    0.9874    37.15 1.068e-04  -6.7820
326201   rs28780090       6_24    0.9870    50.85 1.461e-04   6.8714
147585    rs9834932       3_24    0.9825    66.67 1.906e-04  -8.4816
815091    rs6029132      20_24    0.9824    40.06 1.145e-04  -6.7625
729741    rs4396539      16_37    0.9817    27.62 7.890e-05  -5.2329
626151   rs11057830      12_76    0.9772    26.35 7.493e-05   4.9296
403432    rs3197597       7_61    0.9771    29.60 8.418e-05  -5.0452
815144   rs73124945      20_24    0.9761    32.33 9.185e-05  -7.7754
800719   rs34942359      19_32    0.9738    64.16 1.818e-04  -7.0096
245580  rs114756490      4_100    0.9714    26.44 7.474e-05   4.9889
387664  rs141379002       7_33    0.9684    26.15 7.368e-05   4.8970
469253    rs7024888        9_3    0.9630    26.10 7.315e-05  -5.0558
222851    rs1458038       4_54    0.9621    53.64 1.502e-04  -7.4179
591553   rs11048034       12_9    0.9611    36.81 1.030e-04   6.1337
477117    rs1556516       9_16    0.9603    75.21 2.102e-04  -8.9921
822861   rs62219001       21_2    0.9601    26.60 7.432e-05  -4.9484
759809    rs4969183      17_44    0.9533    50.03 1.388e-04   7.1693
927792    rs1064173       6_26    0.9499    52.05 1.439e-04  -8.8560
620155    rs1196760      12_63    0.9492    26.28 7.260e-05  -4.8667
625016    rs1169300      12_74    0.9475    69.45 1.915e-04   8.6855
78019     rs4076834       2_27    0.9436   442.31 1.215e-03 -20.1086
78016    rs13430143       2_27    0.9435    83.77 2.300e-04  -3.3445
324064   rs75080831       6_19    0.9422    57.91 1.588e-04  -7.9067
325387   rs28986304       6_23    0.9373    42.43 1.157e-04   7.3825
730006    rs9652628      16_38    0.9277   129.58 3.499e-04  11.9505
367364    rs9456502      6_103    0.9179    33.68 8.998e-05   5.9640
746193  rs117859452      17_17    0.9175    24.78 6.617e-05  -3.8517
426313  rs117037226       8_11    0.9160    24.54 6.543e-05   4.1922
800636  rs377297589      19_32    0.9157    51.49 1.372e-04  -6.7865
566550    rs6591179      11_36    0.9154    25.26 6.730e-05   4.8933
70341    rs78610189       2_13    0.9130    60.60 1.610e-04  -8.3855
195374    rs5855544      3_120    0.9113    24.38 6.465e-05  -4.5937
171757     rs189174       3_74    0.9056    42.02 1.107e-04   6.7678
507959   rs10905277       10_8    0.9020    28.31 7.430e-05   5.1258
197161   rs36205397        4_4    0.9000    40.00 1.048e-04   6.1594
725849     rs821840      16_30    0.8993   168.52 4.410e-04 -13.4753
351543   rs12199109       6_73    0.8992    25.50 6.673e-05   4.8570
539797   rs12244851      10_70    0.8962    37.68 9.827e-05  -4.8831
806414   rs74273659       20_5    0.8961    24.89 6.491e-05   4.6468
790613     rs322125      19_10    0.8921   106.99 2.778e-04  -7.4704
635038    rs1012130      13_10    0.8902    41.65 1.079e-04  -2.7810
830102    rs2835302      21_16    0.8845    25.69 6.613e-05  -4.6537
494785    rs2777788       9_53    0.8840    60.76 1.563e-04  -5.7370
579190  rs201912654      11_59    0.8771    40.82 1.042e-04  -6.3056
199386    rs2002574       4_10    0.8765    25.08 6.396e-05  -4.5583
746102    rs3032928      17_17    0.8682    34.31 8.670e-05   6.1119
818643   rs10641149      20_32    0.8662    27.58 6.952e-05   5.0758
123036    rs7569317      2_120    0.8656    43.94 1.107e-04   7.9007
485103   rs11144506       9_35    0.8568    27.27 6.800e-05   5.0427
70141     rs6531234       2_12    0.8466    42.67 1.051e-04  -7.1708
282189    rs3843482       5_44    0.8451   411.33 1.012e-03  25.0344
815109    rs6102034      20_24    0.8450    98.60 2.425e-04 -11.1900
751321    rs4793601      17_28    0.8449    30.91 7.601e-05  -6.2095
813885   rs11167269      20_21    0.8437    59.11 1.451e-04  -7.7950
790582   rs58495388      19_10    0.8431    34.55 8.476e-05   5.5313
357746    rs9321207       6_86    0.8339    31.20 7.572e-05   5.4016
756661    rs9303012      17_39    0.8332   160.79 3.899e-04   2.2591
98706   rs138192199       2_69    0.8266    26.18 6.297e-05   4.6708
903214    rs9884390       4_48    0.8254    70.41 1.691e-04   8.9764
842190  rs145678077      22_17    0.8219    25.69 6.145e-05  -4.8686
635030    rs1799955      13_10    0.8215    73.57 1.759e-04  -6.6936
801631   rs62130338      19_33    0.8116    45.35 1.071e-04   8.4694
831239  rs149577713      21_19    0.8034    30.13 7.044e-05   3.3168
729946   rs12708919      16_38    0.8026   146.26 3.416e-04  11.3028
234747  rs138204164       4_77    0.8016    27.00 6.299e-05  -4.8489
497363    rs2762469       9_56    0.8003    25.88 6.029e-05  -4.5317

SNPs 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
367469   rs3106169      6_104 6.626e-01 56850 1.096e-01 11.139
367470   rs3127598      6_104 4.734e-01 56850 7.833e-02 11.135
367478   rs3106167      6_104 4.782e-01 56850 7.911e-02 11.136
367462  rs11755965      6_104 5.697e-02 56833 9.422e-03 11.140
367473  rs60425481      6_104 1.000e+00 56798 1.653e-01 -7.113
367453  rs12194962      6_104 2.482e-10 56713 4.096e-11 11.106
367471   rs3127597      6_104 5.989e-12 56676 9.877e-13 11.145
367432   rs3119311      6_104 0.000e+00 41129 0.000e+00  8.031
367426   rs3127579      6_104 0.000e+00 29946 0.000e+00  7.568
367420  rs10945658      6_104 0.000e+00 26200 0.000e+00  8.309
367419   rs3119308      6_104 0.000e+00 26136 0.000e+00  8.274
367415   rs3103352      6_104 0.000e+00 26135 0.000e+00  8.522
367411   rs3101821      6_104 0.000e+00 26044 0.000e+00  8.528
367417  rs12205178      6_104 0.000e+00 25988 0.000e+00  8.297
367409 rs148015788      6_104 0.000e+00 25657 0.000e+00  8.351
367520   rs3124784      6_104 0.000e+00 21492 0.000e+00  9.680
367521   rs3127596      6_104 0.000e+00 19498 0.000e+00  9.556
367514   rs3127599      6_104 0.000e+00 19405 0.000e+00  9.259
367484   rs2481030      6_104 0.000e+00 18643 0.000e+00  4.811
367449   rs2504949      6_104 0.000e+00 15359 0.000e+00  2.937
367502    rs388170      6_104 0.000e+00 14217 0.000e+00  3.833
367424    rs316013      6_104 0.000e+00 13630 0.000e+00 -3.002
367425    rs316012      6_104 0.000e+00 13466 0.000e+00 -3.074
367505   rs9355288      6_104 0.000e+00 13158 0.000e+00  6.319
367413    rs610206      6_104 0.000e+00 12446 0.000e+00 -2.944
367414    rs595374      6_104 0.000e+00 12422 0.000e+00 -2.921
367421    rs315995      6_104 0.000e+00 12119 0.000e+00 -3.207
367418    rs543435      6_104 0.000e+00 12073 0.000e+00 -3.250
367467    rs452867      6_104 0.000e+00 11366 0.000e+00 -7.124
367476    rs367334      6_104 0.000e+00 11358 0.000e+00 -7.106
367464    rs589931      6_104 0.000e+00 11356 0.000e+00 -7.116
367465    rs600584      6_104 0.000e+00 11356 0.000e+00 -7.113
367466    rs434953      6_104 0.000e+00 11356 0.000e+00 -7.111
367472    rs380498      6_104 0.000e+00 11356 0.000e+00 -7.115
367440   rs3119312      6_104 0.000e+00 10900 0.000e+00  3.771
367561 rs374071816      6_104 9.996e-01 10391 3.023e-02 16.254
367499   rs2872317      6_104 0.000e+00  9987 0.000e+00  6.746
367496   rs2313453      6_104 0.000e+00  9980 0.000e+00  6.718
367566   rs4252185      6_104 3.618e-04  9573 1.008e-05 15.878
367487 rs146184004      6_104 0.000e+00  9536 0.000e+00  6.534
367490    rs624319      6_104 0.000e+00  9395 0.000e+00 -6.291
367489    rs637614      6_104 0.000e+00  9381 0.000e+00 -6.362
367491    rs486339      6_104 0.000e+00  9317 0.000e+00 -6.311
367436    rs316036      6_104 0.000e+00  9142 0.000e+00 -7.009
367488    rs555754      6_104 0.000e+00  9076 0.000e+00 -6.593
367567  rs12212146      6_104 0.000e+00  7282 0.000e+00 -2.410
367434    rs582280      6_104 0.000e+00  7051 0.000e+00  2.635
367433    rs497039      6_104 0.000e+00  7049 0.000e+00  2.634
367620   rs1247539      6_104 0.000e+00  5711 0.000e+00 -4.294
367517   rs9346818      6_104 0.000e+00  5710 0.000e+00  7.950

SNPs 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
367473  rs60425481      6_104   1.00000 56798.3 0.1652936  -7.1125
367469   rs3106169      6_104   0.66256 56850.4 0.1096180  11.1387
367478   rs3106167      6_104   0.47818 56849.8 0.0791115  11.1356
367470   rs3127598      6_104   0.47345 56849.9 0.0783293  11.1347
367561 rs374071816      6_104   0.99964 10391.1 0.0302291  16.2541
367462  rs11755965      6_104   0.05697 56832.9 0.0094222  11.1396
790529 rs147985405       19_9   0.99882  2357.0 0.0068514 -48.9352
800396    rs814573      19_31   1.00000  2276.8 0.0066258  55.5379
800401  rs12721109      19_31   1.00000  1379.3 0.0040139 -46.3258
857431  rs11591147       1_34   1.00000  1261.3 0.0036706 -39.1649
677728 rs369107859      14_34   1.00000  1054.2 0.0030679  -2.2480
930791  rs67138090       6_27   1.00000   954.1 0.0027767   4.4111
800345  rs62117204      19_31   1.00000   826.5 0.0024052 -44.6722
800398 rs113345881      19_31   1.00000   796.0 0.0023164 -34.3186
800363 rs111794050      19_31   1.00000   784.3 0.0022823 -33.5996
70347     rs548145       2_13   1.00000   679.1 0.0019764  33.0860
677737   rs2159704      14_34   0.47971  1048.1 0.0014632   1.2852
930681   rs9275698       6_27   0.50855   931.1 0.0013780  -0.6590
793039   rs3794991      19_15   1.00000   425.2 0.0012374 -21.4921
78019    rs4076834       2_27   0.94362   442.3 0.0012146 -20.1086
70344     rs934197       2_13   1.00000   414.3 0.0012056  33.0609
282189   rs3843482       5_44   0.84507   411.3 0.0010116  25.0344
961976  rs28601761       8_83   1.00000   343.5 0.0009996 -25.2552
677745   rs7144134      14_34   0.71924   444.1 0.0009296   4.3724
677725   rs7156583      14_34   0.30166  1048.2 0.0009202   1.2485
503009 rs115478735       9_70   1.00000   315.1 0.0009169  19.0118
961992 rs112875651       8_83   0.99990   304.2 0.0008851 -24.2936
790537   rs1569372       19_9   0.99946   294.5 0.0008565  10.0055
367370  rs12208357      6_103   1.00000   256.5 0.0007466  12.2823
790508  rs73013176       19_9   1.00000   247.1 0.0007192 -16.2327
70338    rs1042034       2_13   1.00000   244.9 0.0007127  16.5730
931247   rs2859088       6_27   0.25401   925.4 0.0006841  -0.7222
70424    rs1848922       2_13   1.00000   234.6 0.0006829  25.4123
931229   rs2858883       6_27   0.23764   924.7 0.0006395  -0.7327
282166  rs10062361       5_44   0.98964   210.2 0.0006053  20.3206
857494    rs499883       1_34   0.99970   203.1 0.0005909  16.1075
800104  rs62115478      19_30   1.00000   188.3 0.0005478 -14.3262
72074     rs780093       2_16   1.00000   170.4 0.0004959 -14.1426
756676   rs8070232      17_39   1.00000   166.0 0.0004830  -8.0915
324246 rs115740542       6_20   1.00000   164.3 0.0004783 -12.5323
367384   rs3818678      6_103   0.77137   208.6 0.0004683  -9.9478
725849    rs821840      16_30   0.89926   168.5 0.0004410 -13.4753
756650 rs113408695      17_39   1.00000   151.0 0.0004395  12.7688
582921   rs3135506      11_70   0.99605   151.4 0.0004389  12.3730
70289   rs11679386       2_12   1.00000   146.1 0.0004252  11.9094
756661   rs9303012      17_39   0.83316   160.8 0.0003899   2.2591
677735  rs72627160      14_34   0.12361  1046.8 0.0003766   1.2216
306767  rs12657266       5_92   0.75928   163.1 0.0003604  13.8948
730006   rs9652628      16_38   0.92771   129.6 0.0003499  11.9505
790546 rs137992968       19_9   1.00000   117.6 0.0003424 -10.7526

SNPs 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
800396    rs814573      19_31 1.000e+00 2276.8 6.626e-03  55.54
790529 rs147985405       19_9 9.988e-01 2357.0 6.851e-03 -48.94
790524  rs73015020       19_9 7.011e-04 2344.2 4.783e-06 -48.80
790522 rs138175288       19_9 3.239e-04 2342.4 2.208e-06 -48.78
790523 rs138294113       19_9 7.623e-05 2338.7 5.188e-07 -48.75
790525  rs77140532       19_9 4.559e-05 2338.8 3.103e-07 -48.74
790526 rs112552009       19_9 2.317e-05 2335.4 1.575e-07 -48.71
790527  rs10412048       19_9 8.951e-06 2335.5 6.083e-08 -48.70
790521  rs55997232       19_9 1.369e-09 2315.5 9.228e-12 -48.52
800401  rs12721109      19_31 1.000e+00 1379.3 4.014e-03 -46.33
800345  rs62117204      19_31 1.000e+00  826.5 2.405e-03 -44.67
800332   rs1551891      19_31 0.000e+00  493.9 0.000e+00 -42.27
871774  rs12740374       1_67 2.233e-03  811.9 5.276e-06 -41.79
871770   rs7528419       1_67 5.512e-03  816.9 1.310e-05 -41.74
871781    rs646776       1_67 2.200e-03  812.1 5.199e-06  41.73
871780    rs629301       1_67 1.222e-03  808.7 2.877e-06  41.69
871792    rs583104       1_67 5.479e-04  788.9 1.258e-06  41.09
871795   rs4970836       1_67 5.346e-04  786.6 1.224e-06  41.05
871797   rs1277930       1_67 5.504e-04  785.0 1.257e-06  40.98
871798    rs599839       1_67 5.749e-04  785.9 1.315e-06  40.96
790530  rs17248769       19_9 3.312e-09 1773.3 1.709e-11 -40.84
790531   rs2228671       19_9 2.438e-09 1762.2 1.250e-11 -40.70
871778   rs3832016       1_67 3.170e-04  743.0 6.855e-07  40.40
871775    rs660240       1_67 3.126e-04  738.5 6.718e-07  40.29
871793    rs602633       1_67 3.708e-04  734.5 7.926e-07  39.96
857431  rs11591147       1_34 1.000e+00 1261.3 3.671e-03 -39.16
790520   rs9305020       19_9 2.531e-14 1351.7 9.957e-17 -34.84
800392    rs405509      19_31 0.000e+00  974.3 0.000e+00 -34.64
871761   rs4970834       1_67 7.465e-04  578.3 1.256e-06 -34.62
800398 rs113345881      19_31 1.000e+00  796.0 2.316e-03 -34.32
800316  rs62120566      19_31 0.000e+00 1356.3 0.000e+00 -33.74
800363 rs111794050      19_31 1.000e+00  784.3 2.282e-03 -33.60
70347     rs548145       2_13 1.000e+00  679.1 1.976e-03  33.09
800369   rs4802238      19_31 0.000e+00  980.9 0.000e+00  33.08
70344     rs934197       2_13 1.000e+00  414.3 1.206e-03  33.06
800310 rs188099946      19_31 0.000e+00 1299.9 0.000e+00 -33.04
800380   rs2972559      19_31 0.000e+00 1322.0 0.000e+00  32.29
800304 rs201314191      19_31 0.000e+00 1204.9 0.000e+00 -32.07
871782   rs3902354       1_67 3.652e-04  479.9 5.100e-07  32.00
871771  rs11102967       1_67 3.566e-04  477.2 4.952e-07  31.94
871796   rs4970837       1_67 4.386e-04  481.6 6.148e-07  31.86
800371  rs56394238      19_31 0.000e+00  976.9 0.000e+00  31.55
800348   rs2965169      19_31 0.000e+00  351.4 0.000e+00 -31.38
800372   rs3021439      19_31 0.000e+00  867.1 0.000e+00  31.05
871766    rs611917       1_67 3.102e-04  445.4 4.021e-07 -30.98
70374   rs12997242       2_13 1.061e-11  380.1 1.173e-14  30.82
800379  rs12162222      19_31 0.000e+00 1130.9 0.000e+00  30.50
70348     rs478588       2_13 5.033e-11  626.7 9.180e-14  30.49
800309  rs62119327      19_31 0.000e+00 1060.3 0.000e+00 -30.42
70349   rs56350433       2_13 1.875e-12  350.4 1.912e-15  30.23

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