2 Genomic and Phenotypic Landscape of CCOC models

root.dir <- rprojroot::find_rstudio_root_file()
knitr::opts_chunk$set(echo = TRUE)
knitr::opts_knit$set(root.dir = root.dir )
source(file.path(root.dir,'src/util.R'))
library(DESeq2)
library(dplyr)

CCOC_mutation_table.path <- "data/CCOC_mutation_table.csv"
CCOC_mutation_table <- read.csv(CCOC_mutation_table.path)
CCOC_mutation_table <- CCOC_mutation_table %>% dplyr::mutate(dplyr::across(3:12,as.numeric)) %>% dplyr::mutate( across(where(is.numeric), ~coalesce(., 0))) %>% dplyr::mutate( cell_line= factor(cell_line))

## Warning in mask$eval_all_mutate(quo): NAs introduced by coercion

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## Warning in mask$eval_all_mutate(quo): NAs introduced by coercion

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rownames(CCOC_mutation_table) <- CCOC_mutation_table$cell_line

select.CCOC.marker <-c("PI3K","ARID1A", "HNF1B")
#CCOC.marker.gene <- c("HNF1B", "PAX8", "PPP1R3B", "ARID1A","ARID1B","PTEN", "WT1")

CCOC_Glycogen_Assay_combined.path <- "data/CCOC_Glycogen_Assay_combined.csv"
CCOC_Glycogen_Assay_combined <- read.csv(CCOC_Glycogen_Assay_combined.path)
CCOC_Glycogen_Assay_combined$cell_line <- sapply(CCOC_Glycogen_Assay_combined$sample,function(x){str_replace_all(x,"-[0-9]$","")})
CCOC.Gly <- CCOC_Glycogen_Assay_combined %>% mutate(c = rowMeans(dplyr::select(., starts_with("concentration")))) %>% group_by(cell_line) %>%dplyr::summarize(gly.mean = mean(c, na.rm=TRUE))