Test ambiguous z-score options
shengqian
2023-10-13
Last updated: 2023-11-07
Checks: 6 1
Knit directory: cTWAS_analysis/
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Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
There are no past versions. Publish this analysis with wflow_publish() to start tracking its development.
LDL GWAS with Liver eQTL
load “none” option
load “drop” option
#load "drop" option
ctwas_res <- data.table::fread(paste0(results_dir, runtag,"LDR_drop.susieIrss.txt"))
ctwas_gene_res <- ctwas_res[ctwas_res$type!="SNP",]
drop_pip <- ctwas_gene_res[,c("id","susie_pip")]
drop_z <- get(load(paste0(results_dir, runtag, "LDR_drop_z_gene.Rd")))load “recover” option
#load "recover" option
ctwas_res <- data.table::fread(paste0(results_dir, runtag,"LDR_recover.susieIrss.txt"))
ctwas_gene_res <- ctwas_res[ctwas_res$type!="SNP",]
recover_pip <- ctwas_gene_res[,c("id","susie_pip")]
recover_z <- get(load(paste0(results_dir, runtag, "LDR_recover_z_gene.Rd")))plot z-scores “none” vs “drop”
plot(none_z$z,drop_z$z)
plot z-scores “none” vs “recover”
plot(none_z$z,recover_z$z)
plot z-scores “recover” vs “drop”
plot(recover_z$z,drop_z$z)
plot PIPs “none” vs “drop”
plot(none_pip$susie_pip,drop_pip$susie_pip)
plot PIPs “none” vs “recover”
plot(none_pip$susie_pip,recover_pip$susie_pip)
plot PIPs “recover” vs “drop”
plot(recover_pip$susie_pip,drop_pip$susie_pip)
Xiaotong Joint model
load “none” option
load “drop” option
#load cTWAS results
ctwas_res <- data.table::fread("/project2/xinhe/shared_data/tosheng/brain_ctwas.susieIrss_drop.txt")
ctwas_gene_res <- ctwas_res[ctwas_res$type!="SNP",]
drop_pip <- ctwas_gene_res[,c("id","susie_pip")]
drop_z <- get(load("/project2/xinhe/shared_data/tosheng/brain_expr_z_gene_drop.Rd"))load “recover” option
#load cTWAS results
ctwas_res <- data.table::fread("/project2/xinhe/shared_data/tosheng/brain_ctwas.susieIrss_recover.txt")
ctwas_gene_res <- ctwas_res[ctwas_res$type!="SNP",]
recover_pip <- ctwas_gene_res[,c("id","susie_pip")]
recover_z <- get(load("/project2/xinhe/shared_data/tosheng/brain_expr_z_gene_recover.Rd"))plot z-scores “none” vs “drop”
plot(none_z$z,drop_z$z)
plot z-scores “none” vs “recover”
plot(none_z$z,recover_z$z)
plot z-scores “recover” vs “drop”
plot(recover_z$z,drop_z$z)
plot PIPs “none” vs “drop”
plot(none_pip$susie_pip, drop_pip$susie_pip)
plot PIPs “none” vs “recover”
plot(none_pip$susie_pip,recover_pip$susie_pip)
plot PIPs “recover” vs “drop”
plot(recover_pip$susie_pip,drop_pip$susie_pip)
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] workflowr_1.7.0
loaded via a namespace (and not attached):
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[9] tools_4.1.0 getPass_0.2-2 digest_0.6.31 jsonlite_1.8.4
[13] evaluate_0.19 lifecycle_1.0.3 tibble_3.1.8 pkgconfig_2.0.3
[17] rlang_1.1.1 cli_3.6.1 rstudioapi_0.14 yaml_2.3.6
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[29] rprojroot_2.0.3 data.table_1.14.6 glue_1.6.2 R6_2.5.1
[33] processx_3.8.0 fansi_1.0.3 rmarkdown_2.19 callr_3.7.3
[37] magrittr_2.0.3 whisker_0.4.1 ps_1.7.2 promises_1.2.0.1
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[45] cachem_1.0.6