Single weight simulation
shengqian
2024-5-6
Last updated: 2024-05-09
Checks: 6 1
Knit directory: multigroup_ctwas_analysis/
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| File | Version | Author | Date | Message |
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| Rmd | eb70fef | sq-96 | 2024-05-09 | update |
| html | eb70fef | sq-96 | 2024-05-09 | update |
| Rmd | dc11252 | sq-96 | 2024-05-09 | update single tissue simulation |
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| Rmd | ade62aa | sq-96 | 2024-05-06 | add single weight simulation |
| html | ade62aa | sq-96 | 2024-05-06 | add single weight simulation |
| Rmd | a00c2c8 | sq-96 | 2024-05-06 | add single weight simulation |
| html | a00c2c8 | sq-96 | 2024-05-06 | add single weight simulation |
This single weight simulation study is conducted to evaluate our new cTWAS software performance (parameter estimation, PIP calibration …). Three expression weights from PredictDB are used in this study, which are Liver, Adipose and Lung. Gene PVE is 3% and SNP PVE is 30%. Gene prior is 0.9% and SNP prior is 0.025%. For each weight, I select causal genes, simulate phenotype/GWAS and perform ctwas analysis. Two types of LD between weight SNPs (calculating gene z score) are used and compared in this study. And their performance are very close because most genes only have one weight SNP.
Simulation 1: Expression trait in liver with 3% PVE and 0.9% Prior
Number of causal genes detected (GTEX LD)
simutag ctwas_genes ctwas_cgenes twas_genes twas_cgenes total_cgenes
1 1-1 20 19 57 24 73
2 1-2 15 13 58 22 67
3 1-3 21 20 55 23 74
4 1-4 29 25 68 30 76
5 1-5 16 15 45 21 64Number of causal genes detected (UKBB LD)
simutag ctwas_genes ctwas_cgenes twas_genes twas_cgenes total_cgenes
1 1-1 20 19 57 24 73
2 1-2 16 14 59 23 67
3 1-3 22 20 56 23 74
4 1-4 30 26 69 30 76
5 1-5 16 15 45 21 64Estimated Prior Inclusion Probability and PVE
PIP Calibration Plot based on GTEX LD (filter out cs index 0)
PIP Calibration Plot based on UKBB LD (filter out cs index 0)
| Version | Author | Date |
|---|---|---|
| a00c2c8 | sq-96 | 2024-05-06 |
Simulation 2: Expression trait in adipose with 3% PVE and 0.9% Prior
Number of causal genes detected (GTEX LD)
simutag ctwas_genes ctwas_cgenes twas_genes twas_cgenes total_cgenes
1 1-1 11 11 70 25 90
2 1-2 14 14 54 21 75
3 1-3 25 19 93 27 91
4 1-4 19 17 62 21 92
5 1-5 15 13 56 19 86Number of causal genes detected (UKBB LD)
simutag ctwas_genes ctwas_cgenes twas_genes twas_cgenes total_cgenes
1 1-1 11 11 70 25 90
2 1-2 14 13 56 21 75
3 1-3 24 19 92 27 91
4 1-4 17 16 63 22 92
5 1-5 14 13 56 19 86Estimated Prior Inclusion Probability and PVE
PIP Calibration Plot based on GTEX LD (filter out cs index 0)
PIP Calibration Plot based on UKBB LD (filter out cs index 0)
| Version | Author | Date |
|---|---|---|
| a00c2c8 | sq-96 | 2024-05-06 |
Simulation 3: Expression trait in lung with 3% PVE and 0.9% Prior
Number of causal genes detected (GTEX LD)
simutag ctwas_genes ctwas_cgenes twas_genes twas_cgenes total_cgenes
1 1-1 17 15 87 29 89
2 1-2 14 12 83 22 79
3 1-3 26 19 98 29 97
4 1-4 25 21 51 26 89
5 1-5 23 18 63 28 87Number of causal genes detected (UKBB LD)
simutag ctwas_genes ctwas_cgenes twas_genes twas_cgenes total_cgenes
1 1-1 17 16 88 29 89
2 1-2 15 13 85 22 79
3 1-3 25 19 97 29 97
4 1-4 23 21 52 26 89
5 1-5 21 18 63 28 87Estimated Prior Inclusion Probability and PVE
PIP Calibration Plot based on GTEX LD (filter out cs index 0)
PIP Calibration Plot based on UKBB LD (filter out cs index 0)
| Version | Author | Date |
|---|---|---|
| a00c2c8 | sq-96 | 2024-05-06 |
sessionInfo()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
[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] dplyr_1.1.4 plyr_1.8.7 plotrix_3.8-2 cowplot_1.1.1
[5] ggpubr_0.6.0 ggplot2_3.4.4 ctwas_0.2.0.9004 workflowr_1.7.0
loaded via a namespace (and not attached):
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[3] lazyeval_0.2.2 BiocParallel_1.30.3
[5] GenomeInfoDb_1.32.2 LDlinkR_1.4.0
[7] digest_0.6.29 foreach_1.5.2
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