BMI - Brain Nucleus accumbens basal ganglia
sheng Qian
2021-2-6
Last updated: 2022-02-13
Checks: 6 1
Knit directory: cTWAS_analysis/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | eb13ecf | sq-96 | 2022-02-13 | update |
| html | e6bc169 | sq-96 | 2022-02-13 | Build site. |
| Rmd | 87fee8b | sq-96 | 2022-02-13 | update |
Weight QC
[1] 11487
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1134 801 689 451 561 646 551 431 414 460 695 611 220 384 375 529
17 18 19 20 21 22
672 184 903 357 131 288 [1] 9066[1] 0.78924Load ctwas results
Check convergence of parameters
********************************************************Note: As of version 1.0.0, cowplot does not change the default ggplot2 theme anymore. To recover the previous behavior, execute:
theme_set(theme_cowplot())********************************************************
| Version | Author | Date |
|---|---|---|
| e6bc169 | sq-96 | 2022-02-13 |
gene snp
0.0080450365 0.0002899309 gene snp
20.23213 17.56895 [1] 336107[1] 11487 7535010 gene snp
0.005562868 0.114194849 [1] 0.05015945 17.88795499Genes with highest PIPs
| Version | Author | Date |
|---|---|---|
| e6bc169 | sq-96 | 2022-02-13 |
genename region_tag susie_pip mu2 PVE z
8160 SMAD3 15_31 0.9999995 8015.87282 2.384916e-02 -2.852677
9866 TMIE 3_33 0.9989779 34.99719 1.040187e-04 -7.091659
3378 CCND2 12_4 0.9648998 28.86368 8.286217e-05 -5.119990
9479 NIM1K 5_28 0.9385399 3262.53413 9.110249e-03 5.550554
7777 ZNF12 7_9 0.9363982 27.17655 7.571420e-05 5.127453
13756 NOL12 22_15 0.8990493 61.44780 1.643661e-04 -4.510837
7320 TAL1 1_29 0.7874439 49.34191 1.156001e-04 -6.865849
1678 NINL 20_19 0.7830803 32.87526 7.659455e-05 -5.599931
12851 CYP2A6 19_28 0.7799696 21.54230 4.999105e-05 -3.989619
13574 RP11-108M9.6 1_12 0.7771895 28.35156 6.555809e-05 -4.914590
7010 NBL1 1_13 0.7555923 34.04073 7.652597e-05 -5.638117
4404 TUBG1 17_25 0.7230289 30.27122 6.511904e-05 -5.660250
13759 RP11-823E8.3 12_54 0.7000492 103.65878 2.159022e-04 -6.438012
4137 PODXL 7_80 0.6950352 26.19268 5.416382e-05 4.018009
9422 SOX11 2_4 0.6665243 26.52941 5.260971e-05 4.517012
7829 YWHAZ 8_69 0.6475680 22.77961 4.388884e-05 4.235328
5519 CDH13 16_46 0.6397455 23.81304 4.532570e-05 -4.826363
1132 RRN3 16_15 0.6239131 22.13907 4.109661e-05 4.374275
12949 RP11-566J3.2 14_52 0.6215001 34.21108 6.326019e-05 -5.489252
2821 SENP6 6_52 0.6090897 25.38256 4.599801e-05 -4.618392
num_eqtl
8160 2
9866 2
3378 1
9479 2
7777 2
13756 2
7320 1
1678 2
12851 1
13574 1
7010 1
4404 1
13759 1
4137 1
9422 1
7829 1
5519 1
1132 1
12949 1
2821 2Genes with largest effect sizes
| Version | Author | Date |
|---|---|---|
| e6bc169 | sq-96 | 2022-02-13 |
genename region_tag susie_pip mu2 PVE z
10604 SLC38A3 3_35 0.000000e+00 68425.51 0.000000e+00 6.725828
7846 CCDC171 9_13 0.000000e+00 52440.50 0.000000e+00 7.972850
7671 CAMKV 3_35 0.000000e+00 52028.02 0.000000e+00 -9.574047
2153 PIK3R2 19_14 0.000000e+00 47754.62 0.000000e+00 -7.140312
36 RBM6 3_35 0.000000e+00 41375.93 0.000000e+00 12.536042
7673 MST1R 3_35 0.000000e+00 35329.04 0.000000e+00 -12.622779
9620 STX19 3_59 0.000000e+00 31328.70 0.000000e+00 -5.059656
5542 NOB1 16_37 0.000000e+00 25284.54 0.000000e+00 2.762572
10375 GSAP 7_49 0.000000e+00 24182.56 0.000000e+00 5.119800
5442 MFAP1 15_16 4.268919e-12 23938.26 3.040415e-13 4.302998
7668 RNF123 3_35 0.000000e+00 23402.76 0.000000e+00 -10.957103
5264 TMOD3 15_21 0.000000e+00 22653.47 0.000000e+00 -4.222248
5446 LYSMD2 15_21 0.000000e+00 22304.53 0.000000e+00 -4.402599
1353 WDR76 15_16 0.000000e+00 21497.96 0.000000e+00 4.808984
901 MCM6 2_80 0.000000e+00 18037.55 0.000000e+00 -3.886179
2155 PDE4C 19_14 0.000000e+00 17890.71 0.000000e+00 6.667721
5158 TUBGCP4 15_16 0.000000e+00 16376.38 0.000000e+00 3.554938
1434 MAST3 19_14 0.000000e+00 15938.64 0.000000e+00 -2.208055
9613 NSUN3 3_59 0.000000e+00 15791.55 0.000000e+00 4.755360
8457 LCMT2 15_16 0.000000e+00 14934.90 0.000000e+00 -2.861302
num_eqtl
10604 1
7846 2
7671 2
2153 1
36 1
7673 2
9620 1
5542 1
10375 3
5442 1
7668 1
5264 1
5446 1
1353 2
901 1
2155 1
5158 2
1434 1
9613 1
8457 1Genes with highest PVE
genename region_tag susie_pip mu2 PVE z
8160 SMAD3 15_31 0.99999954 8015.87282 2.384916e-02 -2.852677
9479 NIM1K 5_28 0.93853991 3262.53413 9.110249e-03 5.550554
13498 CTC-498M16.4 5_52 0.05807462 5398.39878 9.327683e-04 7.882989
10849 TTC30B 2_107 0.26101401 752.00020 5.839884e-04 -3.137443
7062 ADPGK 15_34 0.08467030 1200.49261 3.024217e-04 5.925192
13759 RP11-823E8.3 12_54 0.70004918 103.65878 2.159022e-04 -6.438012
10660 SKOR1 15_31 0.60657759 97.95638 1.767834e-04 -9.879755
13756 NOL12 22_15 0.89904930 61.44780 1.643661e-04 -4.510837
7320 TAL1 1_29 0.78744386 49.34191 1.156001e-04 -6.865849
9866 TMIE 3_33 0.99897790 34.99719 1.040187e-04 -7.091659
13962 DHRS11 17_22 0.53374351 61.96358 9.839920e-05 -8.128326
8419 ATXN2L 16_23 0.36166789 77.22963 8.310294e-05 -10.702325
3378 CCND2 12_4 0.96489977 28.86368 8.286217e-05 -5.119990
5575 C18orf8 18_12 0.48218671 57.70858 8.279004e-05 7.477424
1678 NINL 20_19 0.78308033 32.87526 7.659455e-05 -5.599931
7010 NBL1 1_13 0.75559234 34.04073 7.652597e-05 -5.638117
7777 ZNF12 7_9 0.93639821 27.17655 7.571420e-05 5.127453
5380 SUOX 12_35 0.53798979 47.10209 7.539398e-05 -5.190773
385 PHLPP2 16_38 0.57430624 41.84005 7.149212e-05 4.618775
13574 RP11-108M9.6 1_12 0.77718948 28.35156 6.555809e-05 -4.914590
num_eqtl
8160 2
9479 2
13498 1
10849 1
7062 3
13759 1
10660 2
13756 2
7320 1
9866 2
13962 1
8419 1
3378 1
5575 2
1678 2
7010 1
7777 2
5380 1
385 1
13574 1Genes with largest z scores
genename region_tag susie_pip mu2 PVE z
7673 MST1R 3_35 0.0000000000 35329.04340 0.000000e+00 -12.622779
36 RBM6 3_35 0.0000000000 41375.93494 0.000000e+00 12.536042
7668 RNF123 3_35 0.0000000000 23402.76132 0.000000e+00 -10.957103
8554 INO80E 16_24 0.0316645156 99.46356 9.370425e-06 10.886319
8419 ATXN2L 16_23 0.3616678947 77.22963 8.310294e-05 -10.702325
10629 CLN3 16_23 0.0417000087 75.23465 9.334187e-06 10.363250
10875 C6orf106 6_28 0.0000256066 120.40834 9.173411e-09 -10.263559
12178 NPIPB7 16_23 0.0366258145 74.39248 8.106601e-06 10.037986
8218 ZNF668 16_24 0.1121179514 77.18576 2.574748e-05 10.000364
10660 SKOR1 15_31 0.6065775943 97.95638 1.767834e-04 -9.879755
9435 NFATC2IP 16_23 0.0457742783 75.97829 1.034745e-05 -9.863387
4330 ZC3H4 19_33 0.0052482859 98.99347 1.545776e-06 9.848747
1906 KAT8 16_24 0.0170220382 72.06602 3.649762e-06 -9.785239
1905 BCKDK 16_24 0.0124311403 68.64839 2.539006e-06 9.637985
11636 NDUFS3 11_29 0.0131019911 84.88855 3.309092e-06 -9.629039
7671 CAMKV 3_35 0.0000000000 52028.02173 0.000000e+00 -9.574047
8924 C1QTNF4 11_29 0.0113720906 83.81941 2.836007e-06 9.563515
11640 LAT 16_23 0.0724465661 77.05500 1.660891e-05 -9.552834
10852 FAM180B 11_29 0.0108339097 82.28414 2.652307e-06 -9.489956
2550 MTCH2 11_29 0.0105269672 81.10908 2.540359e-06 -9.432202
num_eqtl
7673 2
36 1
7668 1
8554 2
8419 1
10629 2
10875 1
12178 1
8218 1
10660 2
9435 1
4330 1
1906 1
1905 1
11636 2
7671 2
8924 1
11640 1
10852 1
2550 1Comparing z scores and PIPs
| Version | Author | Date |
|---|---|---|
| e6bc169 | sq-96 | 2022-02-13 |
| Version | Author | Date |
|---|---|---|
| e6bc169 | sq-96 | 2022-02-13 |
[1] 0.02002263 genename region_tag susie_pip mu2 PVE z
7673 MST1R 3_35 0.0000000000 35329.04340 0.000000e+00 -12.622779
36 RBM6 3_35 0.0000000000 41375.93494 0.000000e+00 12.536042
7668 RNF123 3_35 0.0000000000 23402.76132 0.000000e+00 -10.957103
8554 INO80E 16_24 0.0316645156 99.46356 9.370425e-06 10.886319
8419 ATXN2L 16_23 0.3616678947 77.22963 8.310294e-05 -10.702325
10629 CLN3 16_23 0.0417000087 75.23465 9.334187e-06 10.363250
10875 C6orf106 6_28 0.0000256066 120.40834 9.173411e-09 -10.263559
12178 NPIPB7 16_23 0.0366258145 74.39248 8.106601e-06 10.037986
8218 ZNF668 16_24 0.1121179514 77.18576 2.574748e-05 10.000364
10660 SKOR1 15_31 0.6065775943 97.95638 1.767834e-04 -9.879755
9435 NFATC2IP 16_23 0.0457742783 75.97829 1.034745e-05 -9.863387
4330 ZC3H4 19_33 0.0052482859 98.99347 1.545776e-06 9.848747
1906 KAT8 16_24 0.0170220382 72.06602 3.649762e-06 -9.785239
1905 BCKDK 16_24 0.0124311403 68.64839 2.539006e-06 9.637985
11636 NDUFS3 11_29 0.0131019911 84.88855 3.309092e-06 -9.629039
7671 CAMKV 3_35 0.0000000000 52028.02173 0.000000e+00 -9.574047
8924 C1QTNF4 11_29 0.0113720906 83.81941 2.836007e-06 9.563515
11640 LAT 16_23 0.0724465661 77.05500 1.660891e-05 -9.552834
10852 FAM180B 11_29 0.0108339097 82.28414 2.652307e-06 -9.489956
2550 MTCH2 11_29 0.0105269672 81.10908 2.540359e-06 -9.432202
num_eqtl
7673 2
36 1
7668 1
8554 2
8419 1
10629 2
10875 1
12178 1
8218 1
10660 2
9435 1
4330 1
1906 1
1905 1
11636 2
7671 2
8924 1
11640 1
10852 1
2550 1Sensitivity, specificity and precision for silver standard genes
[1] 41[1] 24[1] 4.593787[1] 6[1] 230 genename region_tag susie_pip mu2 PVE z num_eqtl
8160 SMAD3 15_31 0.9999995 8015.8728 0.0238491585 -2.852677 2
13756 NOL12 22_15 0.8990493 61.4478 0.0001643661 -4.510837 2 ctwas TWAS
0.00000000 0.04878049 ctwas TWAS
0.9994766 0.9801099 ctwas TWAS
0.000000000 0.008695652 
| Version | Author | Date |
|---|---|---|
| e6bc169 | sq-96 | 2022-02-13 |
sessionInfo()R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.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] readxl_1.3.1 cowplot_1.0.0 ggplot2_3.3.5 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] tidyselect_1.1.1 xfun_0.29 purrr_0.3.4 colorspace_2.0-2
[5] vctrs_0.3.8 generics_0.1.1 htmltools_0.5.2 yaml_2.2.1
[9] utf8_1.2.2 blob_1.2.2 rlang_0.4.12 jquerylib_0.1.4
[13] later_0.8.0 pillar_1.6.4 glue_1.5.1 withr_2.4.3
[17] DBI_1.1.1 bit64_4.0.5 lifecycle_1.0.1 stringr_1.4.0
[21] cellranger_1.1.0 munsell_0.5.0 gtable_0.3.0 evaluate_0.14
[25] memoise_2.0.1 labeling_0.4.2 knitr_1.36 fastmap_1.1.0
[29] httpuv_1.5.1 fansi_0.5.0 highr_0.9 Rcpp_1.0.7
[33] promises_1.0.1 scales_1.1.1 cachem_1.0.6 farver_2.1.0
[37] fs_1.5.2 bit_4.0.4 digest_0.6.29 stringi_1.7.6
[41] dplyr_1.0.7 rprojroot_2.0.2 grid_3.6.1 tools_3.6.1
[45] magrittr_2.0.1 tibble_3.1.6 RSQLite_2.2.8 crayon_1.4.2
[49] whisker_0.3-2 pkgconfig_2.0.3 ellipsis_0.3.2 data.table_1.14.2
[53] assertthat_0.2.1 rmarkdown_2.11 R6_2.5.1 git2r_0.26.1
[57] compiler_3.6.1