nanopore read assessment

With your nanopore reads stored on a suitable machine, you can analyze them with several phylochemistry functions. Here is a quick overview:

qc_data <- fastxQC(
    paths_to_fastxs = c(
        "/Users/bust0037/Documents/Science/Websites/thebustalab.github.io/data/example.fastq",
        "/Users/bust0037/Documents/Science/Websites/thebustalab.github.io/data/example2.fastq"
    ),
    type = "fasta",
    mode = "slow",
    max_n_seqs = 1000
)

head(qc_data)

qc_data %>%
  mutate(category = case_when(
    length > mean(qc_data$length)*5 ~ "chromosome",
    length <= mean(qc_data$length)*5 ~ "leftover_bit"
  )) %>%
  ggplot() +
    geom_treemap(aes(area = length, fill = category), color = "black", size = 1) +
    scale_fill_manual(values = c("gold", "maroon"))