mmplot_cov_profiles: Compare coverage profiles
In KasperSkytte/mmgenome2: Tools for extracting individual genomes from metagenomes

Description Usage Arguments Value Examples

Plots all coverage profiles in the data for comparison. This is useful for identifying scaffold patterns across multiple coverage profiles and spot potential contaminants.

mmplot_cov_profiles(
  mm,
  normalise = FALSE,
  alpha = 0.6,
  color_by = NULL,
  color_vector = c("blue", "green", "red"),
  color_scale_log10 = FALSE,
  y_scale_log10 = FALSE,
  plot_lines = TRUE,
  interactive_plot = FALSE,
  mm_normalise = NULL,
  mm_normalise_index = NULL
)

`mm`	(required) A dataframe loaded with `mmload`.
`normalise`	(Logical) Normalises each coverage column in `mm` to its highest value and multiplies by 100. (Default: `TRUE`)
`alpha`	The transparancy of the scaffold points and lines, where 0 is invisible and 1 is opaque. (Default: `0.6`)
`color_by`	Color the scaffolds by a variable in `mm`. (Default: `NULL`)
`color_vector`	The colors from which to generate a color gradient when `color_by` is set and the variable is continuous. Any number of colors can be used. (Default: `c("blue", "green", "red")`)
`color_scale_log10`	(Logical) Log10-scale the color gradient when `color_by` is set and the variable is continuous. (Default: `FALSE`)
`y_scale_log10`	(Logical) Log10-scale the y axis. (Default: `FALSE`)
`plot_lines`	(Logical) Connect scaffolds with lines. (Default: `TRUE`)
`interactive_plot`	(Logical) Return an interactive `plotly` plot or not. (Default: `FALSE`)
`mm_normalise`	A dataframe loaded with `mmload` to normalise by.
`mm_normalise_index`	A coverage column to serve as an index for normalisation.

A ggplot or plotly object. Note that mmgenome2 hides all warnings produced by ggplot objects.

library(mmgenome2)
data(mmgenome2)
mmgenome2
selection <- data.frame(
  cov_C13.11.25 = c(7.2, 16.2, 25.2, 23.3, 10.1),
  cov_C14.01.09 = c(47, 77, 52.8, 29.5, 22.1)
)
mmgenome2_extraction <- mmextract(mmgenome2,
  min_length = 3000,
  selection = selection,
  inverse = FALSE
)
mmplot_cov_profiles(mmgenome2_extraction,
  color_by = "taxonomy",
  normalise = FALSE
)