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pangenome_alpha.R
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pangenome_alpha.R
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library(data.table)
library(tidyverse)
library(micropan)
df <- fread("~/Downloads/gene_presence_absence.csv") %>% as_tibble()
pa <- data.matrix(df[,15:ncol(df)]!='')
heap_df <- map_dfr(1:1000, ~{
ppa <- pa[sample(nrow(pa), replace = FALSE), sample(ncol(pa), replace = FALSE)]
cumlative <- rowSums(apply(ppa, 1, cumsum)>0)
cumlative <- cumlative-cumlative[[1]]
df <- tibble(N = 1:length(cumlative),
naccessory = cumlative)
res <- lm(nunique ~ logN, tibble(logN = log(1:length(cumlative)),
nunique = log(cumlative+0.001)))
return(df %>%
add_column(logK=res$coefficients[[1]]) %>%
add_column(beta=res$coefficients[[2]]) %>%
add_column(permutation=.x, .before = 1))
})
coefs <- heap_df[!duplicated(heap_df$permutation),]
q <- quantile(coefs$beta, c(0.5, 0.025, 0.975))
plotdf <- heap_df %>% group_by(N) %>%
summarise(
`accessory size` = mean(naccessory),
std = sd(naccessory)
)
ggplot(plotdf, aes(N, `accessory size`)) +
geom_ribbon(aes(ymin = `accessory size` - std,
ymax = `accessory size` + std),
fill='#67a9cf', alpha=0.5) +
geom_line(size = 1, col='#b2182b') +
theme_bw(base_size = 14) +
xlab("Number of genomes") +
ylab("Accessory size") +
geom_label(x = 5, y = 90,
label = sprintf("α = %.2f (%.2f, %.2f)", q[[1]], q[[2]], q[[3]]),
size=5)
ggsave("~/Downloads/E_faecalis_pangenome_alpha.pdf", width = 12, height = 7, device = cairo_pdf)
ggsave("~/Downloads/E_faecalis_pangenome_alpha.png", width = 12, height = 7)