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Knit directory: multigroup_ctwas_analysis/
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library(ctwas)
library(dplyr)
load("/project2/xinhe/shared_data/multigroup_ctwas/gwas/samplesize.rdata")trait <- "IBD-ebi-a-GCST004131"
baseline_tissue <- c("Whole_Blood","Colon_Sigmoid","Colon_Transverse")
gwas_n <- samplesize[trait]
result_dir <- paste0("/project/xinhe/xsun/multi_group_ctwas/12.tissue_selection/results/", trait, "/")
extra_tissue <- list.files(path = result_dir)
extra_tissue <- extra_tissue[-which(extra_tissue == "baseline")]
all <- c()
for (tissue in c("baseline",extra_tissue)) {
para_file <- paste0(result_dir,tissue,"/",trait,"_",tissue,".param.RDS")
param <- readRDS(para_file)
ctwas_parameters <- summarize_param(param, gwas_n)
if(tissue == "baseline") {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g_baseline <- (1- ctwas_parameters$prop_heritability["SNP"])*100
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g_baseline,NA,prob_h2g,total_pve,NA)
}else {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g <- (1- ctwas_parameters$prop_heritability["SNP"])*100
nonSNP_prob_h2g_gain <- total_nonSNP_prob_h2g - total_nonSNP_prob_h2g_baseline
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue,tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g,nonSNP_prob_h2g_gain,prob_h2g,total_pve,NA)
}
all <- rbind(all,h2g_v_tissue)
}
colnames(all) <- c("extra_tissue","total_nonSNP_prob_h2g(%)","nonSNP_prob_h2g_gain(%)",paste0("%h2g_",c(baseline_tissue)),"%h2g_extra_tissue","pve_gain")
all <- as.data.frame(all)
all <- all %>%
dplyr::mutate(across(where(is.character), ~ as.numeric(.x))) %>% # Convert character columns to numeric
dplyr::mutate(across(where(is.numeric), ~ round(.x, digits = 4))) # Round numeric columns
all$extra_tissue <- c("baseline",extra_tissue)
rownames(all) <- seq(1:nrow(all))
DT::datatable(all,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black; font-size:150% ;','PVE change after adding extra tissue'),options = list(pageLength = 10) )trait <- "IBD-ebi-a-GCST004131"
baseline_tissue <- c("Whole_Blood","Colon_Sigmoid","Colon_Transverse","Artery_Coronary")
gwas_n <- samplesize[trait]
result_dir <- paste0("/project/xinhe/xsun/multi_group_ctwas/12.tissue_selection/results/", trait,"_round2", "/")
extra_tissue <- list.files(path = result_dir)
extra_tissue <- extra_tissue[-which(extra_tissue == "baseline")]
all <- c()
for (tissue in c("baseline",extra_tissue)) {
para_file <- paste0(result_dir,tissue,"/",trait,"_",tissue,".param.RDS")
param <- readRDS(para_file)
ctwas_parameters <- summarize_param(param, gwas_n)
if(tissue == "baseline") {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g_baseline <- (1- ctwas_parameters$prop_heritability["SNP"])*100
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g_baseline,NA,prob_h2g,total_pve,NA)
}else {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g <- (1- ctwas_parameters$prop_heritability["SNP"])*100
nonSNP_prob_h2g_gain <- total_nonSNP_prob_h2g - total_nonSNP_prob_h2g_baseline
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue,tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g,nonSNP_prob_h2g_gain,prob_h2g,total_pve,NA)
}
all <- rbind(all,h2g_v_tissue)
}
colnames(all) <- c("extra_tissue","total_nonSNP_prob_h2g(%)","nonSNP_prob_h2g_gain(%)",paste0("%h2g_",c(baseline_tissue)),"%h2g_extra_tissue","pve_gain")
all <- as.data.frame(all)
all <- all %>%
dplyr::mutate(across(where(is.character), ~ as.numeric(.x))) %>% # Convert character columns to numeric
dplyr::mutate(across(where(is.numeric), ~ round(.x, digits = 4))) # Round numeric columns
all$extra_tissue <- c("baseline",extra_tissue)
rownames(all) <- seq(1:nrow(all))
DT::datatable(all,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black; font-size:150% ;','PVE change after adding extra tissue'),options = list(pageLength = 10) )trait <- "IBD-ebi-a-GCST004131"
baseline_tissue <- c("Whole_Blood","Colon_Sigmoid","Colon_Transverse","Artery_Coronary","Heart_Left_Ventricle")
gwas_n <- samplesize[trait]
result_dir <- paste0("/project/xinhe/xsun/multi_group_ctwas/12.tissue_selection/results/", trait,"_round3", "/")
extra_tissue <- list.files(path = result_dir)
extra_tissue <- extra_tissue[-which(extra_tissue == "baseline")]
all <- c()
for (tissue in c("baseline",extra_tissue)) {
para_file <- paste0(result_dir,tissue,"/",trait,"_",tissue,".param.RDS")
param <- readRDS(para_file)
ctwas_parameters <- summarize_param(param, gwas_n)
if(tissue == "baseline") {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g_baseline <- (1- ctwas_parameters$prop_heritability["SNP"])*100
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g_baseline,NA,prob_h2g,total_pve,NA)
}else {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g <- (1- ctwas_parameters$prop_heritability["SNP"])*100
nonSNP_prob_h2g_gain <- total_nonSNP_prob_h2g - total_nonSNP_prob_h2g_baseline
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue,tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g,nonSNP_prob_h2g_gain,prob_h2g,total_pve,NA)
}
all <- rbind(all,h2g_v_tissue)
}
colnames(all) <- c("extra_tissue","total_nonSNP_prob_h2g(%)","nonSNP_prob_h2g_gain(%)",paste0("%h2g_",c(baseline_tissue)),"%h2g_extra_tissue","pve_gain")
all <- as.data.frame(all)
all <- all %>%
dplyr::mutate(across(where(is.character), ~ as.numeric(.x))) %>% # Convert character columns to numeric
dplyr::mutate(across(where(is.numeric), ~ round(.x, digits = 4))) # Round numeric columns
all$extra_tissue <- c("baseline",extra_tissue)
rownames(all) <- seq(1:nrow(all))
DT::datatable(all,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black; font-size:150% ;','PVE change after adding extra tissue'),options = list(pageLength = 10) )trait <- "IBD-ebi-a-GCST004131"
baseline_tissue <- c("Whole_Blood","Colon_Sigmoid","Colon_Transverse","Artery_Coronary","Heart_Left_Ventricle","Cells_Cultured_fibroblasts")
gwas_n <- samplesize[trait]
result_dir <- paste0("/project/xinhe/xsun/multi_group_ctwas/12.tissue_selection/results/", trait,"_round4", "/")
extra_tissue <- list.files(path = result_dir)
extra_tissue <- extra_tissue[-which(extra_tissue == "baseline")]
all <- c()
for (tissue in c("baseline",extra_tissue)) {
para_file <- paste0(result_dir,tissue,"/",trait,"_",tissue,".param.RDS")
param <- readRDS(para_file)
ctwas_parameters <- summarize_param(param, gwas_n)
if(tissue == "baseline") {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g_baseline <- (1- ctwas_parameters$prop_heritability["SNP"])*100
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g_baseline,NA,prob_h2g,total_pve,NA)
}else {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g <- (1- ctwas_parameters$prop_heritability["SNP"])*100
nonSNP_prob_h2g_gain <- total_nonSNP_prob_h2g - total_nonSNP_prob_h2g_baseline
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue,tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g,nonSNP_prob_h2g_gain,prob_h2g,total_pve,NA)
}
all <- rbind(all,h2g_v_tissue)
}
colnames(all) <- c("extra_tissue","total_nonSNP_prob_h2g(%)","nonSNP_prob_h2g_gain(%)",paste0("%h2g_",c(baseline_tissue)),"%h2g_extra_tissue","pve_gain")
all <- as.data.frame(all)
all <- all %>%
dplyr::mutate(across(where(is.character), ~ as.numeric(.x))) %>% # Convert character columns to numeric
dplyr::mutate(across(where(is.numeric), ~ round(.x, digits = 4))) # Round numeric columns
all$extra_tissue <- c("baseline",extra_tissue)
rownames(all) <- seq(1:nrow(all))
DT::datatable(all,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black; font-size:150% ;','PVE change after adding extra tissue'),options = list(pageLength = 10) )trait <- "SBP-ukb-a-360"
baseline_tissue <- c("Artery_Aorta", "Heart_Left_Ventricle", "Adrenal_Gland")
gwas_n <- samplesize[trait]
result_dir <- paste0("/project/xinhe/xsun/multi_group_ctwas/12.tissue_selection/results/", trait, "/")
extra_tissue <- list.files(path = result_dir)
extra_tissue <- extra_tissue[-which(extra_tissue == "baseline")]
all <- c()
for (tissue in c("baseline",extra_tissue)) {
para_file <- paste0(result_dir,tissue,"/",trait,"_",tissue,".param.RDS")
param <- readRDS(para_file)
ctwas_parameters <- summarize_param(param, gwas_n)
if(tissue == "baseline") {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g_baseline <- (1- ctwas_parameters$prop_heritability["SNP"])*100
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g_baseline,NA,prob_h2g,total_pve,NA)
}else {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g <- (1- ctwas_parameters$prop_heritability["SNP"])*100
nonSNP_prob_h2g_gain <- total_nonSNP_prob_h2g - total_nonSNP_prob_h2g_baseline
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue,tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g,nonSNP_prob_h2g_gain,prob_h2g,total_pve,NA)
}
all <- rbind(all,h2g_v_tissue)
}
colnames(all) <- c("extra_tissue","total_nonSNP_prob_h2g(%)","nonSNP_prob_h2g_gain(%)",paste0("%h2g_",c(baseline_tissue)),"%h2g_extra_tissue","pve_gain")
all <- as.data.frame(all)
all <- all %>%
dplyr::mutate(across(where(is.character), ~ as.numeric(.x))) %>% # Convert character columns to numeric
dplyr::mutate(across(where(is.numeric), ~ round(.x, digits = 4))) # Round numeric columns
all$extra_tissue <- c("baseline",extra_tissue)
rownames(all) <- seq(1:nrow(all))
DT::datatable(all,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black; font-size:150% ;','PVE change after adding extra tissue'),options = list(pageLength = 10) )baseline_tissue <- c("Artery_Aorta", "Heart_Left_Ventricle", "Adrenal_Gland","Brain_Cortex")
gwas_n <- samplesize[trait]
result_dir <- paste0("/project/xinhe/xsun/multi_group_ctwas/12.tissue_selection/results/", trait,"_round2", "/")
extra_tissue <- list.files(path = result_dir)
extra_tissue <- extra_tissue[-which(extra_tissue == "baseline")]
all <- c()
for (tissue in c("baseline",extra_tissue)) {
para_file <- paste0(result_dir,tissue,"/",trait,"_",tissue,".param.RDS")
param <- readRDS(para_file)
ctwas_parameters <- summarize_param(param, gwas_n)
if(tissue == "baseline") {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g_baseline <- (1- ctwas_parameters$prop_heritability["SNP"])*100
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g_baseline,NA,prob_h2g,total_pve,NA)
}else {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g <- (1- ctwas_parameters$prop_heritability["SNP"])*100
nonSNP_prob_h2g_gain <- total_nonSNP_prob_h2g - total_nonSNP_prob_h2g_baseline
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue,tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g,nonSNP_prob_h2g_gain,prob_h2g,total_pve,NA)
}
all <- rbind(all,h2g_v_tissue)
}
colnames(all) <- c("extra_tissue","total_nonSNP_prob_h2g(%)","nonSNP_prob_h2g_gain(%)",paste0("%h2g_",c(baseline_tissue)),"%h2g_extra_tissue","pve_gain")
all <- as.data.frame(all)
all <- all %>%
dplyr::mutate(across(where(is.character), ~ as.numeric(.x))) %>% # Convert character columns to numeric
dplyr::mutate(across(where(is.numeric), ~ round(.x, digits = 4))) # Round numeric columns
all$extra_tissue <- c("baseline",extra_tissue)
rownames(all) <- seq(1:nrow(all))
DT::datatable(all,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black; font-size:150% ;','PVE change after adding extra tissue'),options = list(pageLength = 10) )trait <- "SBP-ukb-a-360"
baseline_tissue <- c("Artery_Aorta", "Artery_Tibial", "Adrenal_Gland")
gwas_n <- samplesize[trait]
result_dir <- paste0("/project/xinhe/xsun/multi_group_ctwas/12.tissue_selection/results/", trait, "_base2/")
extra_tissue <- list.files(path = result_dir)
extra_tissue <- extra_tissue[-which(extra_tissue == "baseline")]
all <- c()
for (tissue in c("baseline",extra_tissue)) {
para_file <- paste0(result_dir,tissue,"/",trait,"_",tissue,".param.RDS")
param <- readRDS(para_file)
ctwas_parameters <- summarize_param(param, gwas_n)
if(tissue == "baseline") {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g_baseline <- (1- ctwas_parameters$prop_heritability["SNP"])*100
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g_baseline,NA,prob_h2g,total_pve,NA)
}else {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g <- (1- ctwas_parameters$prop_heritability["SNP"])*100
nonSNP_prob_h2g_gain <- total_nonSNP_prob_h2g - total_nonSNP_prob_h2g_baseline
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue,tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g,nonSNP_prob_h2g_gain,prob_h2g,total_pve,NA)
}
all <- rbind(all,h2g_v_tissue)
}
colnames(all) <- c("extra_tissue","total_nonSNP_prob_h2g(%)","nonSNP_prob_h2g_gain(%)",paste0("%h2g_",c(baseline_tissue)),"%h2g_extra_tissue","pve_gain")
all <- as.data.frame(all)
all <- all %>%
dplyr::mutate(across(where(is.character), ~ as.numeric(.x))) %>% # Convert character columns to numeric
dplyr::mutate(across(where(is.numeric), ~ round(.x, digits = 4))) # Round numeric columns
all$extra_tissue <- c("baseline",extra_tissue)
rownames(all) <- seq(1:nrow(all))
DT::datatable(all,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black; font-size:150% ;','PVE change after adding extra tissue'),options = list(pageLength = 10) )baseline_tissue <- c("Artery_Aorta", "Heart_Left_Ventricle", "Adrenal_Gland","Brain_Cortex")
gwas_n <- samplesize[trait]
result_dir <- paste0("/project/xinhe/xsun/multi_group_ctwas/12.tissue_selection/results/", trait, "_base2_round2", "/")
extra_tissue <- list.files(path = result_dir)
extra_tissue <- extra_tissue[-which(extra_tissue == "baseline")]
all <- c()
for (tissue in c("baseline",extra_tissue)) {
para_file <- paste0(result_dir,tissue,"/",trait,"_",tissue,".param.RDS")
param <- readRDS(para_file)
ctwas_parameters <- summarize_param(param, gwas_n)
if(tissue == "baseline") {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g_baseline <- (1- ctwas_parameters$prop_heritability["SNP"])*100
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g_baseline,NA,prob_h2g,total_pve,NA)
}else {
total_pve <- ctwas_parameters$total_pve
total_nonSNP_prob_h2g <- (1- ctwas_parameters$prop_heritability["SNP"])*100
nonSNP_prob_h2g_gain <- total_nonSNP_prob_h2g - total_nonSNP_prob_h2g_baseline
prob_h2g <- round(as.numeric(ctwas_parameters$prop_heritability[paste0(c(baseline_tissue,tissue),"|eQTL")]*100),digits = 4)
h2g_v_tissue <- c(tissue, total_nonSNP_prob_h2g,nonSNP_prob_h2g_gain,prob_h2g,total_pve,NA)
}
all <- rbind(all,h2g_v_tissue)
}
colnames(all) <- c("extra_tissue","total_nonSNP_prob_h2g(%)","nonSNP_prob_h2g_gain(%)",paste0("%h2g_",c(baseline_tissue)),"%h2g_extra_tissue","pve_gain")
all <- as.data.frame(all)
all <- all %>%
dplyr::mutate(across(where(is.character), ~ as.numeric(.x))) %>% # Convert character columns to numeric
dplyr::mutate(across(where(is.numeric), ~ round(.x, digits = 4))) # Round numeric columns
all$extra_tissue <- c("baseline",extra_tissue)
rownames(all) <- seq(1:nrow(all))
DT::datatable(all,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black; font-size:150% ;','PVE change after adding extra tissue'),options = list(pageLength = 10) )
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] C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] dplyr_1.1.4 ctwas_0.4.19
loaded via a namespace (and not attached):
[1] colorspace_2.0-3 rjson_0.2.21
[3] ellipsis_0.3.2 rprojroot_2.0.3
[5] XVector_0.36.0 locuszoomr_0.2.1
[7] GenomicRanges_1.48.0 fs_1.5.2
[9] rstudioapi_0.13 DT_0.22
[11] ggrepel_0.9.1 bit64_4.0.5
[13] AnnotationDbi_1.58.0 fansi_1.0.3
[15] xml2_1.3.3 codetools_0.2-18
[17] logging_0.10-108 cachem_1.0.6
[19] knitr_1.39 jsonlite_1.8.0
[21] workflowr_1.7.0 Rsamtools_2.12.0
[23] dbplyr_2.1.1 png_0.1-7
[25] readr_2.1.2 compiler_4.2.0
[27] httr_1.4.3 assertthat_0.2.1
[29] Matrix_1.5-3 fastmap_1.1.0
[31] lazyeval_0.2.2 cli_3.6.1
[33] later_1.3.0 htmltools_0.5.2
[35] prettyunits_1.1.1 tools_4.2.0
[37] gtable_0.3.0 glue_1.6.2
[39] GenomeInfoDbData_1.2.8 rappdirs_0.3.3
[41] Rcpp_1.0.12 Biobase_2.56.0
[43] jquerylib_0.1.4 vctrs_0.6.5
[45] Biostrings_2.64.0 rtracklayer_1.56.0
[47] crosstalk_1.2.0 xfun_0.41
[49] stringr_1.5.1 lifecycle_1.0.4
[51] irlba_2.3.5 restfulr_0.0.14
[53] ensembldb_2.20.2 XML_3.99-0.14
[55] zlibbioc_1.42.0 zoo_1.8-10
[57] scales_1.3.0 gggrid_0.2-0
[59] hms_1.1.1 promises_1.2.0.1
[61] MatrixGenerics_1.8.0 ProtGenerics_1.28.0
[63] parallel_4.2.0 SummarizedExperiment_1.26.1
[65] AnnotationFilter_1.20.0 LDlinkR_1.2.3
[67] yaml_2.3.5 curl_4.3.2
[69] memoise_2.0.1 ggplot2_3.5.1
[71] sass_0.4.1 biomaRt_2.54.1
[73] stringi_1.7.6 RSQLite_2.3.1
[75] S4Vectors_0.34.0 BiocIO_1.6.0
[77] GenomicFeatures_1.48.3 BiocGenerics_0.42.0
[79] filelock_1.0.2 BiocParallel_1.30.3
[81] GenomeInfoDb_1.39.9 rlang_1.1.2
[83] pkgconfig_2.0.3 matrixStats_0.62.0
[85] bitops_1.0-7 evaluate_0.15
[87] lattice_0.20-45 purrr_1.0.2
[89] GenomicAlignments_1.32.0 htmlwidgets_1.5.4
[91] cowplot_1.1.1 bit_4.0.4
[93] tidyselect_1.2.0 magrittr_2.0.3
[95] R6_2.5.1 IRanges_2.30.0
[97] generics_0.1.2 DelayedArray_0.22.0
[99] DBI_1.2.2 withr_2.5.0
[101] pgenlibr_0.3.3 pillar_1.9.0
[103] whisker_0.4 KEGGREST_1.36.3
[105] RCurl_1.98-1.7 mixsqp_0.3-43
[107] tibble_3.2.1 crayon_1.5.1
[109] utf8_1.2.2 BiocFileCache_2.4.0
[111] plotly_4.10.0 tzdb_0.4.0
[113] rmarkdown_2.25 progress_1.2.2
[115] grid_4.2.0 data.table_1.14.2
[117] blob_1.2.3 git2r_0.30.1
[119] digest_0.6.29 tidyr_1.3.0
[121] httpuv_1.6.5 stats4_4.2.0
[123] munsell_0.5.0 viridisLite_0.4.0
[125] bslib_0.3.1