| plotBins | R Documentation | 
This function selects the most abundant bins across all samples in a SQM object and represents their abundances in a barplot. Alternatively, a custom set of bins can be represented.
plotBins(
  SQM,
  count = "percent",
  N = 15,
  bins = NULL,
  others = TRUE,
  samples = NULL,
  ignore_unmapped = FALSE,
  ignore_nobin = FALSE,
  rescale = FALSE,
  color = NULL,
  base_size = 11,
  max_scale_value = NULL,
  metadata_groups = NULL
)
| SQM | A SQM object. | 
| count | character. Either  | 
| N | integer Plot the  | 
| bins | character. Custom bins to plot. If provided, it will override  | 
| others | logical. Collapse the abundances of least abundant bins, and include the result in the plot (default  | 
| samples | character. Character vector with the names of the samples to include in the plot. Can also be used to plot the samples in a custom order. If not provided, all samples will be plotted (default  | 
| ignore_unmapped | logical. Don't include unmapped reads in the plot (default  | 
| ignore_nobin | logical. Don't include reads which are not in a bin in the plot (default  | 
| rescale | logical. Re-scale results to percentages (default  | 
| color | Vector with custom colors for the different features. If empty, we will use our own hand-picked pallete if N<=15, and the default ggplot2 palette otherwise (default  | 
| base_size | numeric. Base font size (default  | 
| max_scale_value | numeric. Maximum value to include in the y axis. By default it is handled automatically by ggplot2 (default  | 
| metadata_groups | list. Split the plot into groups defined by the user: list('G1' = c('sample1', sample2'), 'G2' = c('sample3', 'sample4')) default  | 
a ggplot2 plot object.
plotTaxonomy for plotting the most abundant taxa of a SQM object; plotBars and plotHeatmap for plotting barplots or heatmaps with arbitrary data.
data(Hadza)
# Bins distribution.
plotBins(Hadza)
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