A testrun for MAGMA
Jing Gu
2024-09-19
Last updated: 2024-09-19
Checks: 7 0
Knit directory: lung_lymph_scMultiomics/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 1e7e576 | Jing Gu | 2024-09-19 | look into k5 genes with high z scores |
| html | ab42a52 | Jing Gu | 2024-09-16 | Build site. |
| Rmd | a2b320f | Jing Gu | 2024-09-16 | test topic enrichment for genetic risks |
MAGMA
Gene analysis A linear principal component regression model that estimates whether there is genetic effect of gene g on the phenotype Y, conditional on all covariates. The model first projects genotype matrix for a gene g onto its PCs, pruning away PCs with very small eigenvalues. Then it performs F test in the regression of Y on SNP matrix and covariates to estimate genetic effect.
\[ Y = \alpha_{0g}\vec 1 + X_g^*\alpha_g + W\beta_g + \epsilon_g \] When inividual geneotype matrix not available, MAGMA performs gene test with mean \(X^2\) statistics and a gene p-value is then obtained by using a known approximation of the sampling distribution. Please refer to the following paper for details of approximation for the distribution of the weighted combination of p-values. This model requires summary statistics and reference LD panel.
Hou C (2005) A simple approximation for the distribution of the weighted combination of non-independent or independent probabilities. Stat Probabil Lett 73: 179–187.
Competitive gene-set analysis
One-sided Two-sample T test or linear regression in equivalence is applied to test whether the genes in a gene set are more strongly associated with Y or not.
Let Z denote the association z-score. Let \(\S_s\) be an indicator variable with element \(s_g = 1\) defined as for gene g in gene set s and 0 otherwise. The goal is to test whether \(\beta_s\) is greater than zero, which represents the difference in association between genes in the gene set and genes outside the gene set.
\[ Z = \beta_{0s}\vec 1 + S_s\beta_s + \epsilon \] This also be tested by unpaired two sample T-test, while two samples can have unequal variances and sample sizes.
Testrun
Procedure:
- annotate SNPs and genes
- gene-based analysis
- gene-set analysis
Results
When corrected for multiple testing, tests will be significant if p-value lower than ~0.005. Around half of the tests show significant p-values, which makes us wonder if p-values are inflated. Then we try using the input genes for topic modeling rather than all genes as background so that they are more comparable.
- Total number of genes reduced from to 18K to ~16K
- P values for the reduced background genes are very similar to the full ones.
| Version | Author | Date |
|---|---|---|
| ab42a52 | Jing Gu | 2024-09-16 |
Test enrichment using top 100 genes from each topic
The supplementary table from MAGMA paper shows the mean type 1 error
rates are well controlled for a set of size 100. The MSigDB
canonical pathways contains 1320 gene sets from a number of
different databases. I can look into the average size of the gene sets.
Instead of all DE genes, I used top 100 up-regulated genes ranked by z scores to test the enrichment for each topic. Now we see only k3, k4, k5 and k12 (4/12) topics show significant enrichment after multiple testing correction.
Check the top genes contributing to topic 5 that have high MAGMA Z-scores
Genes with high Z-scores (p < 0.05) are found to show enrichment in the following gene sets:
- Regulation of signal transduction (adj.P = 0.01) from GO
- RORA, GATA3, CDC42SE2, SREBF2
- Interleukin-2 signaling pathway (adj.P = 0.003) from BioPlanet
- CD247, RORA, GATA3, TAB2, FOXO1,IL21R, YARS (overlapping genes)
- Th17 Cell Differentiation (adj.P = 0.0002) and IBD (adj.P = 0.001)
from KEGG
- CD247, RORA, GATA3,IL21R
Joining with `by = join_by(GENE)` X_SET4_ GENE CHR START STOP NSNPS NPARAM N ZSTAT
1 _SET4_ 60468 6 90636247 91006627 1026 117 336782 8.45050000
2 _SET4_ 919 1 167399877 167487847 355 73 336782 6.84930000
3 _SET4_ 2625 10 8087294 8117164 147 28 336782 6.12250000
4 _SET4_ 6095 15 60780483 61521502 2789 298 336782 5.60430000
5 _SET4_ 115426 9 6413151 6507054 357 33 336782 4.79490000
6 _SET4_ 340152 6 149768766 149806148 214 19 336782 4.01200000
7 _SET4_ 56990 5 130599702 130730383 280 35 336782 2.90970000
8 _SET4_ 23118 6 149639436 149732747 335 25 336782 2.78020000
9 _SET4_ 50615 16 27413483 27463363 229 57 336782 2.64820000
10 _SET4_ 10666 18 67530192 67624412 378 59 336782 2.36120000
11 _SET4_ 10318 5 150409504 150467221 256 43 336782 2.23780000
12 _SET4_ 6721 22 42229083 42303312 221 39 336782 2.18420000
13 _SET4_ 2308 13 41129801 41240734 323 29 336782 2.15450000
14 _SET4_ 1362 17 28705942 28796675 160 23 336782 1.73580000
15 _SET4_ 51230 20 34359923 34538292 585 24 336782 1.73200000
16 _SET4_ 23387 11 116714118 116969131 1087 35 336782 1.55350000
17 _SET4_ 8565 1 33240840 33283633 108 22 336782 1.55560000
18 _SET4_ 54331 14 52327022 52436518 577 66 336782 1.51080000
19 _SET4_ 59343 3 185300284 185348889 146 15 336782 1.33270000
20 _SET4_ 55833 9 33921691 34048947 497 32 336782 1.09100000
21 _SET4_ 2534 6 111981535 112194655 815 52 336782 1.04560000
22 _SET4_ 7879 3 128444975 128533641 327 29 336782 1.09670000
23 _SET4_ 678 2 43449541 43453745 13 7 336782 1.06920000
24 _SET4_ 23253 18 9136751 9285983 528 35 336782 1.05670000
25 _SET4_ 26136 7 115850547 115898840 180 17 336782 0.96789000
26 _SET4_ 51742 1 235330210 235491532 504 23 336782 0.93847000
27 _SET4_ 8556 1 100810598 100985833 444 38 336782 0.96840000
28 _SET4_ 9267 17 76670130 76778376 319 27 336782 0.94589000
29 _SET4_ 3685 2 187454058 187545629 201 39 336782 0.84031000
30 _SET4_ 23198 2 54091204 54197977 404 36 336782 0.85629000
31 _SET4_ 257415 7 92190072 92219706 86 18 336782 0.93003000
32 _SET4_ 57488 7 158523688 158622729 519 25 336782 0.85795000
33 _SET4_ 94120 6 159065931 159185908 546 66 336782 0.74631000
34 _SET4_ 5430 17 7387698 7417935 153 16 336782 0.78662000
35 _SET4_ 90268 5 14664783 14699842 89 21 336782 0.80570000
36 _SET4_ 8887 7 27778992 27869386 267 35 336782 0.74946000
37 _SET4_ 5906 1 112162405 112256807 420 36 336782 0.65849000
38 _SET4_ 4676 11 2965660 3013607 222 32 336782 0.56302000
39 _SET4_ 27436 2 42396490 42559688 630 31 336782 0.42312000
40 _SET4_ 51430 1 172501494 172580973 167 35 336782 0.33426000
41 _SET4_ 7409 19 6772679 6857377 332 55 336782 0.32158000
42 _SET4_ 3607 17 80477594 80562483 419 49 336782 0.25939000
43 _SET4_ 2288 12 2904108 2914589 11 4 336782 0.39082000
44 _SET4_ 56829 7 138728266 138794466 212 34 336782 0.19810000
45 _SET4_ 4603 8 67474410 67525484 113 18 336782 0.46371000
46 _SET4_ 9043 17 49039535 49198226 394 41 336782 0.24384000
47 _SET4_ 1106 15 93442286 93571237 485 46 336782 0.09673500
48 _SET4_ 923 11 60739113 60787849 230 49 336782 0.09332900
49 _SET4_ 80714 19 19672516 19729725 214 20 336782 0.20781000
50 _SET4_ 23074 12 100422233 100536642 395 37 336782 0.16546000
51 _SET4_ 10260 15 65952954 66084631 364 27 336782 0.09866700
52 _SET4_ 6775 2 191894302 192037404 407 56 336782 0.03275800
53 _SET4_ 284996 2 101887681 101925178 87 24 336782 -0.00084963
54 _SET4_ 10383 9 140135711 140138159 9 5 336782 0.27720000
55 _SET4_ 26051 20 37434348 37551667 411 72 336782 0.00594630
56 _SET4_ 6497 1 2160134 2241652 346 69 336782 -0.04317000
57 _SET4_ 58508 7 151832010 152133090 377 20 336782 0.13412000
58 _SET4_ 6732 6 35800811 35888957 295 23 336782 -0.04915800
59 _SET4_ 23130 11 64662004 64684722 62 11 336782 0.05085400
60 _SET4_ 4929 2 157180944 157189287 9 5 336782 -0.09094000
61 _SET4_ 29072 3 47057898 47205467 277 26 336782 -0.15736000
62 _SET4_ 8027 10 17686124 17758823 359 21 336782 -0.12647000
63 _SET4_ 60481 6 53132196 53213977 279 19 336782 -0.16222000
64 _SET4_ 9728 15 49280835 49338760 140 22 336782 -0.19923000
65 _SET4_ 80331 20 62526455 62567384 192 28 336782 -0.18511000
66 _SET4_ 51429 6 158137078 158366109 970 58 336782 -0.28369000
67 _SET4_ 54622 5 53180578 53606403 1813 122 336782 -0.27789000
68 _SET4_ 2776 9 80335189 80646219 863 57 336782 -0.29571000
69 _SET4_ 4928 11 3696240 3819022 430 33 336782 -0.28774000
70 _SET4_ 27161 8 141541264 141645646 467 68 336782 -0.42633000
71 _SET4_ 567 15 45003685 45010357 13 5 336782 -0.27618000
72 _SET4_ 63916 20 44994689 45035690 72 17 336782 -0.35065000
73 _SET4_ 253959 14 36007558 36278432 574 32 336782 -0.42536000
74 _SET4_ 960 11 35160417 35253949 413 73 336782 -0.50107000
75 _SET4_ 9585 10 91461264 91534700 315 19 336782 -0.49604000
76 _SET4_ 53405 6 45866188 46048085 739 90 336782 -0.54930000
77 _SET4_ 868 3 105374306 105589354 743 45 336782 -0.56987000
78 _SET4_ 7293 1 1146706 1149703 11 5 336782 -0.40596000
79 _SET4_ 79572 3 194123403 194188968 187 23 336782 -0.48753000
80 _SET4_ 5599 10 49514682 49647403 398 37 336782 -0.58362000
81 _SET4_ 26191 1 114356433 114414375 144 30 336782 -0.65354000
82 _SET4_ 55031 11 11862970 11980872 403 41 336782 -0.67810000
83 _SET4_ 125488 18 21572737 21715574 507 57 336782 -0.72006000
84 _SET4_ 5604 15 66679182 66783882 374 33 336782 -0.72970000
85 _SET4_ 1499 3 41236401 41281939 99 22 336782 -0.78735000
86 _SET4_ 829 1 113162075 113214241 121 29 336782 -0.85602000
87 _SET4_ 26524 13 21547175 21635722 325 32 336782 -0.87000000
88 _SET4_ 23347 18 2655886 2805015 678 33 336782 -0.95213000
89 _SET4_ 58476 20 33292147 33301240 19 10 336782 -1.04680000
90 _SET4_ 2782 1 1716725 1822552 217 39 336782 -1.08390000
91 _SET4_ 285513 4 90162427 90229161 237 44 336782 -1.14290000
92 _SET4_ 6935 10 31607825 31818742 408 30 336782 -0.97917000
93 _SET4_ 4363 16 16043434 16236931 811 67 336782 -1.28210000
94 _SET4_ 23048 9 132649458 132805473 654 46 336782 -1.20560000
95 _SET4_ 9147 14 50250528 50319763 128 41 336782 -1.24380000
96 _SET4_ 8428 13 99102455 99229396 485 46 336782 -1.91380000
P ZFITTED_BASE ZRESID_BASE SYMBOL
1 9.9039e-20 0.0000e+00 8.45050000 BACH2
2 1.0814e-13 0.0000e+00 6.84930000 CD247
3 1.5312e-11 0.0000e+00 6.12250000 GATA3
4 4.0321e-10 0.0000e+00 5.60430000 RORA
5 7.4517e-08 0.0000e+00 4.79490000 UHRF2
6 3.0972e-06 0.0000e+00 4.01200000 ZC3H12D
7 3.9436e-04 4.4409e-16 2.90970000 CDC42SE2
8 5.4278e-04 4.4409e-16 2.78020000 TAB2
9 7.6388e-04 4.4409e-16 2.64820000 IL21R
10 2.3719e-03 4.4409e-16 2.36120000 CD226
11 3.1237e-03 4.4409e-16 2.23780000 TNIP1
12 3.7568e-03 4.4409e-16 2.18420000 SREBF2
13 4.1285e-03 4.4409e-16 2.15450000 FOXO1
14 1.1793e-02 2.2204e-16 1.73580000 CPD
15 1.6984e-02 2.2204e-16 1.73200000 PHF20
16 2.0633e-02 2.2204e-16 1.55350000 SIK3
17 2.0987e-02 2.2204e-16 1.55560000 YARS
18 2.1930e-02 2.2204e-16 1.51080000 GNG2
19 3.5505e-02 2.2204e-16 1.33270000 SENP2
20 5.6123e-02 2.2204e-16 1.09100000 UBAP2
21 6.3251e-02 2.2204e-16 1.04560000 FYN
22 6.5841e-02 2.2204e-16 1.09670000 RAB7A
23 6.6380e-02 2.2204e-16 1.06920000 ZFP36L2
24 6.6452e-02 2.2204e-16 1.05670000 ANKRD12
25 7.2884e-02 2.2204e-16 0.96789000 TES
26 7.4910e-02 2.2204e-16 0.93847000 ARID4B
27 7.7287e-02 2.2204e-16 0.96840000 CDC14A
28 7.8260e-02 2.2204e-16 0.94589000 CYTH1
29 8.5962e-02 2.2204e-16 0.84031000 ITGAV
30 8.6831e-02 2.2204e-16 0.85629000 PSME4
31 9.0951e-02 2.2204e-16 0.93003000 FAM133B
32 9.7966e-02 2.2204e-16 0.85795000 ESYT2
33 1.0373e-01 2.2204e-16 0.74631000 SYTL3
34 1.0565e-01 2.2204e-16 0.78662000 POLR2A
35 1.0827e-01 2.2204e-16 0.80570000 OTULIN
36 1.0937e-01 2.2204e-16 0.74946000 TAX1BP1
37 1.2473e-01 2.2204e-16 0.65849000 RAP1A
38 1.4087e-01 2.2204e-16 0.56302000 NAP1L4
39 1.7093e-01 2.7756e-16 0.42312000 EML4
40 1.9850e-01 2.7756e-16 0.33426000 SUCO
41 2.0326e-01 2.7756e-16 0.32158000 VAV1
42 2.1586e-01 2.7756e-16 0.25939000 FOXK2
43 2.3176e-01 2.7756e-16 0.39082000 FKBP4
44 2.3304e-01 2.7756e-16 0.19810000 ZC3HAV1
45 2.3537e-01 2.7756e-16 0.46371000 MYBL1
46 2.3855e-01 2.7756e-16 0.24384000 SPAG9
47 2.6657e-01 2.6368e-16 0.09673500 CHD2
48 2.7075e-01 2.6368e-16 0.09332900 CD6
49 2.7184e-01 2.7756e-16 0.20781000 PBX4
50 2.8320e-01 2.7756e-16 0.16546000 UHRF1BP1L
51 2.8801e-01 2.6368e-16 0.09866700 DENND4A
52 2.9184e-01 2.6368e-16 0.03275800 STAT4
53 3.0147e-01 2.6476e-16 -0.00084963 RNF149
54 3.1265e-01 2.7756e-16 0.27720000 TUBB4B
55 3.1278e-01 2.6455e-16 0.00594630 PPP1R16B
56 3.2321e-01 2.6368e-16 -0.04317000 SKI
57 3.2898e-01 2.7756e-16 0.13412000 KMT2C
58 3.3295e-01 2.6368e-16 -0.04915800 SRPK1
59 3.4537e-01 2.6368e-16 0.05085400 ATG2A
60 3.6504e-01 2.6368e-16 -0.09094000 NR4A2
61 3.7147e-01 2.7756e-16 -0.15736000 SETD2
62 3.7562e-01 2.7756e-16 -0.12647000 STAM
63 3.7722e-01 2.7756e-16 -0.16222000 ELOVL5
64 3.8339e-01 2.7756e-16 -0.19923000 SECISBP2L
65 3.8868e-01 2.7756e-16 -0.18511000 DNAJC5
66 4.0245e-01 2.7756e-16 -0.28369000 SNX9
67 4.0338e-01 2.7756e-16 -0.27789000 ARL15
68 4.1351e-01 2.7756e-16 -0.29571000 GNAQ
69 4.1970e-01 2.7756e-16 -0.28774000 NUP98
70 4.6964e-01 2.7756e-16 -0.42633000 AGO2
71 4.7298e-01 2.7756e-16 -0.27618000 B2M
72 4.7943e-01 2.7756e-16 -0.35065000 ELMO2
73 5.0369e-01 2.7756e-16 -0.42536000 RALGAPA1
74 5.0731e-01 2.2204e-16 -0.50107000 CD44
75 5.1298e-01 2.7756e-16 -0.49604000 KIF20B
76 5.2310e-01 2.2204e-16 -0.54930000 CLIC5
77 5.2936e-01 2.2204e-16 -0.56987000 CBLB
78 5.3331e-01 2.7756e-16 -0.40596000 TNFRSF4
79 5.3378e-01 2.7756e-16 -0.48753000 ATP13A3
80 5.4428e-01 2.2204e-16 -0.58362000 MAPK8
81 5.5105e-01 2.2204e-16 -0.65354000 PTPN22
82 5.8017e-01 2.2204e-16 -0.67810000 USP47
83 5.9235e-01 2.2204e-16 -0.72006000 TTC39C
84 6.0026e-01 2.2204e-16 -0.72970000 MAP2K1
85 6.0696e-01 2.2204e-16 -0.78735000 CTNNB1
86 6.3320e-01 2.2204e-16 -0.85602000 CAPZA1
87 6.4814e-01 2.2204e-16 -0.87000000 LATS2
88 6.7139e-01 2.2204e-16 -0.95213000 SMCHD1
89 7.1615e-01 2.2204e-16 -1.04680000 TP53INP2
90 7.1974e-01 2.2204e-16 -1.08390000 GNB1
91 7.2113e-01 2.2204e-16 -1.14290000 GPRIN3
92 7.3190e-01 2.2204e-16 -0.97917000 ZEB1
93 7.7264e-01 2.2204e-16 -1.28210000 ABCC1
94 7.7937e-01 2.2204e-16 -1.20560000 FNBP1
95 7.8719e-01 2.2204e-16 -1.24380000 NEMF
96 9.1854e-01 2.2204e-16 -1.91380000 STK24
R version 4.2.0 (2022-04-22)
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 LC_TIME=C
[4] LC_COLLATE=C LC_MONETARY=C LC_MESSAGES=C
[7] LC_PAPER=C LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=C LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] dplyr_1.1.4 data.table_1.15.4 workflowr_1.7.1
loaded via a namespace (and not attached):
[1] Rcpp_1.0.12 highr_0.10 compiler_4.2.0 pillar_1.9.0
[5] bslib_0.7.0 later_1.3.2 git2r_0.33.0 jquerylib_0.1.4
[9] tools_4.2.0 getPass_0.2-2 digest_0.6.35 jsonlite_1.8.8
[13] evaluate_0.23 lifecycle_1.0.4 tibble_3.2.1 pkgconfig_2.0.3
[17] rlang_1.1.3 cli_3.6.2 rstudioapi_0.15.0 crosstalk_1.2.1
[21] yaml_2.3.8 xfun_0.43 fastmap_1.1.1 httr_1.4.7
[25] stringr_1.5.1 knitr_1.46 htmlwidgets_1.6.4 generics_0.1.3
[29] fs_1.6.4 vctrs_0.6.5 sass_0.4.9 DT_0.33
[33] tidyselect_1.2.1 rprojroot_2.0.4 glue_1.7.0 R6_2.5.1
[37] processx_3.8.3 fansi_1.0.6 rmarkdown_2.26 callr_3.7.3
[41] magrittr_2.0.3 whisker_0.4.1 ps_1.7.6 promises_1.3.0
[45] htmltools_0.5.8.1 httpuv_1.6.14 utf8_1.2.4 stringi_1.7.6
[49] cachem_1.0.8