library(subcellularvis)
library(tidyverse)
dat <- data.frame(
rank = c(1:20),
compartment = c(
"Cell junction",
"Chromatin",
"ER membrane",
"Mitochondrial matrix",
"Actin, cytosol",
"ER lumen",
"Endosome, lysosome",
"Nucleolus",
"Nucleoplasm",
"Nuclear body",
"Plasma membrane",
"Centrosome",
"Mitochondrial Membrane, Peroxisome",
"Golgi",
"Nuclear outer membrane-ER membrane network",
"Cytoplasmic RNP granule",
"Microtubules",
"Mitochondrial inner membrane, Mitochondrial inter membrane space",
"Misc.",
"Early endosome, Recycling endosome"
)
)
prey <- readxl::read_excel("~/Supplementary table 8.xlsx", sheet = 2) %>%
pivot_longer(-gene) %>%
group_by(gene) %>%
filter(value== max(value)) %>%
mutate(rank = as.integer(gsub("rank ", "", name))) %>%
select(-c(name, value)) %>%
ungroup() %>%
left_join(dat)
dat_n <- prey %>%
group_by(compartment) %>%
summarise(n_all=n())
subCell_predictions <- prey %>%
group_by(rank) %>%
group_split() %>%
lapply(function(i){
compartmentData(i$gene)$enrichment %>%
slice(1) %>%
#filter(`FDR < 0.05` == T) %>%
mutate(predComp = Compartment,
trueComp = unique(i$compartment))
}) %>%
bind_rows() %>%
left_join(dat_n, by = c("trueComp" = "compartment")) %>%
mutate(n = paste0(n, "/", n_all)) %>%
select(trueComp, predComp, FDR, n)
subCell_predictions_supp <- prey %>%
group_by(rank) %>%
group_split() %>%
lapply(function(i){
compartmentData(i$gene)$enrichment %>%
# slice(1) %>%
#filter(`FDR < 0.05` == T) %>%
mutate(predComp = Compartment,
trueComp = unique(i$compartment))
}) %>%
bind_rows() %>%
filter(FDR < 0.05) %>%
left_join(dat_n, by = c("trueComp" = "compartment")) %>%
mutate(n = paste0(n, "/", n_all)) %>%
select(trueComp, predComp, FDR, n)
readr::write_csv(subCell_predictions, "data-raw/subcellResults_Go_etal_2021.csv")
readr::write_csv(subCell_predictions_supp, "data-raw/subcellResults_Go_etal_2021_supp.csv")
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