In philippmuench/OligoMMR:

devtools::install_github("philippmuench/OligoMMR")

library(OligoMMR)
library(dplyr)
library(tidyr)
library(ComplexHeatmap)
data(oligomm_ab_isolates)
data(oligomm_ab_wgs)

df <- data.frame(
    snp_id = oligomm_ab_isolates$snp_id,
    AF = oligomm_ab_isolates$AF,
    feature = oligomm_ab_isolates$feature,
    genome_hr = oligomm_ab_isolates$genome_hr,
    sample_id = paste0(oligomm_ab_isolates$sample))

head(df)

df_wide <- spread(df, key = sample_id, value = AF)
df_wide[is.na(df_wide)] <- 0
df$num <- 1
df_agg <- aggregate(data = df, num ~ genome_hr + sample_id, FUN = sum)

library(ggplot2)
p <- ggplot(df_agg, aes(x = reorder(genome_hr, num), y = num))
p <- p + geom_boxplot() + geom_jitter(size = 1) + coord_flip()
p <- p + theme_pmuench(base_size = 9) + scale_y_log10()
p <- p + xlab("") + ylab("Number of SNPs in genomic isolates")
p

col_fun <- circlize::colorRamp2(c(0, 0.5, 1), c("white", "orange", "red"))

unique(oligomm_ab_isolates$genome_hr)

Panel A

ht <- OligoMMR::create_heatmap_iso(iso_profile = oligomm_ab_isolates,
  wgs_profile = oligomm_ab_wgs,
  genome_hr = "C. innocuum",
  col_fun = col_fun,
  filtered = T)
ht

philippmuench/OligoMMR documentation built on April 15, 2022, 10:32 a.m.