Single weight simulation
shengqian
2024-5-6
Last updated: 2024-05-06
Checks: 6 1
Knit directory: multigroup_ctwas_analysis/
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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. 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.
Warning: replacing previous import 'utils::download.file' by
'restfulr::download.file' when loading 'rtracklayer'
Attaching package: 'cowplot'The following object is masked from 'package:ggpubr':
get_legend
Attaching package: 'plyr'The following object is masked from 'package:ggpubr':
mutate
Attaching package: 'dplyr'The following objects are masked from 'package:plyr':
arrange, count, desc, failwith, id, mutate, rename, summarise,
summarizeThe following objects are masked from 'package:stats':
filter, lagThe following objects are masked from 'package:base':
intersect, setdiff, setequal, unionSimulation 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
Estimated PVE
PIP Calibration Plot based on UKBB LD (filter out cs index 0)
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
Estimated PVE
PIP Calibration Plot based on UKBB LD (filter out cs index 0)
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
Estimated PVE
PIP Calibration Plot based on UKBB LD (filter out cs index 0)
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_0.2.0.9003 workflowr_1.7.0
loaded via a namespace (and not attached):
[1] backports_1.4.1 BiocFileCache_2.4.0
[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
[9] ensembldb_2.20.2 htmltools_0.5.3
[11] fansi_1.0.3 magrittr_2.0.3
[13] memoise_2.0.1 Biostrings_2.64.0
[15] matrixStats_0.62.0 locuszoomr_0.3.0
[17] prettyunits_1.1.1 colorspace_2.0-3
[19] blob_1.2.3 rappdirs_0.3.3
[21] ggrepel_0.9.4 xfun_0.32
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[35] BiocGenerics_0.42.0 abind_1.4-5
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[103] irlba_2.3.5 httpuv_1.6.5
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