Plot kmer complexity of references sequences of a phyloseq object

Basically a wrapper of dada2::seqComplexity()

Usage

plot_complexity_pq(
  physeq,
  kmer_size = 2,
  window = NULL,
  by = 5,
  bins = 100,
  aggregate = FALSE,
  vline_random_kmer = TRUE,
  ...
)

Arguments

physeq

(required): a phyloseq-class object obtained using the phyloseq package.

kmer_size

int (default 2) The size of the kmers (or "oligonucleotides" or "words") to use.

window

(int, default NULL) The width in nucleotides of the moving window. If NULL the whole sequence is used.

by

(int, default 5) The step size in nucleotides between each moving window tested.

bins

(int, default 100). The number of bins to use for the histogram.

aggregate

(logical, default FALSE) If TRUE, compute an aggregate quality profile for all samples

vline_random_kmer

(logical, default TRUE) If TRUE, add a vertical line at the value for random kmer (equal to 4^kmerSize))

...

Arguments passed on to geom_histogram.

Value

A ggplot2 object

Details

This function is mainly a wrapper of the work of others. Please make a reference to dada2::seqComplexity()

See also

dada2::seqComplexity(), dada2::plotComplexity()

Author

Adrien Taudière

Examples

plot_complexity_pq(subset_samples(data_fungi_mini, Height == "High"),
  vline_random_kmer = FALSE
)

plot_complexity_pq(subset_samples(data_fungi_mini, Height == "Low"),
  aggregate = FALSE, kmer_size = 4
)

# plot_complexity_pq(subset_samples(data_fungi, Height == "Low"), kmer_size = 4)