Read mauve backbone files to create dna_segs and comparisons

Parses Progressive Mauve backbone files to create a list of dna_segs, and a matching list of comparisons between them.

Usage

read_mauve_backbone(
  file,
  ref = 1,
  gene_type = "side_blocks",
  header = TRUE,
  filter_low = 0,
  common_blocks_only = TRUE,
  ...
)

Arguments

file: A character string containing a file path, or a file connection.
ref: A numeric indicating which DNA segment to use as the reference, i.e. which one will have its blocks in order.
gene_type: A character string, determines how genes are visualized. Must be a valid gene type (see gene_types).
header: Logical. If TRUE, parses the first line of the file as a header containing column names.
filter_low: A numeric, if larger than 0, all blocks smaller than this number will be filtered out.
common_blocks_only: Logical. If TRUE, reads only common blocks (core blocks).
...: Further arguments to pass to as.dna_seg.

Value

A list with 2 named elements: dna_segs and comparisons, which are both lists containing the dna_seg and comparison objects, respectively.

Details

Mauve Backbone files are tabular files that summarize similarities between genomes in blocks. Each genome has 2 columns containing the start and end coordinates of each block, respectively. The header, if present, uses sequence numbers instead of genome names. See https://darlinglab.org/mauve/user-guide/files.html for more info on the file format. This function should be able to read both progressiveMauve and mauveAligner outputs.

References

Mauve: https://darlinglab.org/mauve/mauve.html

Author

Lionel Guy, Jens Roat Kultima

Examples

## Mauve backbone
bbone_file <- system.file('extdata/barto.backbone', package = 'genoPlotR')
bbone <- read_mauve_backbone(bbone_file)
names <- c("B_bacilliformis", "B_grahamii", "B_henselae", "B_quintana")
names(bbone$dna_segs) <- names

## Plot
plot_gene_map(dna_segs = bbone$dna_segs, comparisons = bbone$comparisons)


## Using filter_low & changing reference sequence
bbone <- read_mauve_backbone(bbone_file, ref = 2, filter_low = 2000) 
names(bbone$dna_segs) <- names
plot_gene_map(dna_segs = bbone$dna_segs, comparisons = bbone$comparisons)