# karyogram <- function(nmr, chr_info) {
# assert_has_columns(chr_info, c("chr", "length"))
#
# n_chr <- nrow(chr_info)
# plots <- list()
#
# widest <- max(chr_info$length)
#
# for (i in 1:n_chr) {
# m <- query_methy(nmr, chr_info$chr[i], 1, chr_info$length[i])
#
# bins <- round(seq(1, chr_info$length[i], length.out = 2^10))
#
# bin_means <- binMeans(m$statistic > 0, x = m$pos, bx = bins)
#
# df <- tibble(
# pos = bins[-length(bins)],
# methy_prop = as.numeric(bin_means),
# count = attr(bin_means, "count")
# )
#
# plots[[i]] <- ggplot(df, aes(x = pos, y = 1, fill = methy_prop)) +
# geom_tile() +
# scico::scale_colour_scico(palette = 'imola', direction = -1) +
# theme_void() +
# theme(plot.margin = margin(0, 2, 0, 0)) +
# ggtitle(chr_info$chr[i]) +
# xlim(1, widest)
# }
#
# patchwork::wrap_plots(plots, ncol = 1, guides = "collect")
# }
#
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