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Module I · Chord

1.1 Tables and field meanings1.2 Produce and import comparisons1.3 Build the layers step by step1.4 Direction, curvature and clearance1.5 Filter and summarize links1.6 Full source-file workflow1.7 Complete chord showcase

Module II · Collinear

2.1 Reuse chord input tables2.2 Switch coordinates and add layers2.3 Routes, clearance and the ruler2.4 Compare CDS neighbourhoods2.5 Focus, anchors and segments2.6 Complete collinear showcase

Module III · Plasmid

3.1 DNA, annotations and 13 references3.2 From a circle to annotation layers3.3 Features, primers and restriction3.4 Thirteen plasmid references3.5 Complete plasmid cases

Consult as needed · Data and layers

Prepare tables and coordinatesImport and convert dataImport nucleotide and protein alignmentsProject protein intervals to genomic coordinatesFeatures, stacking and genomic decorationLabels and local placementQuantitative tracksMappings, scales, guides and themesSet values by sequence and strandCommon adjustments and grammarExport, preview and diagnostics

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Focus quantitative intervals or samples without bridging omitted windows

On this page

• Usage
• Arguments
• Value
• See also
• Examples

Applies the same explicit loci and output IDs as focus_ggchord_data() and segment_ggchord_data(). It never averages, interpolates, rescales values, or creates boundary samples. Missing values remain missing. Subsequent track layers group by the returned window accession, so separate windows cannot be joined by a line. Source coordinates and original row lineage survive repeated focusing.

Usage

Code

focus_ggchord_track(
  data,
  seq_data,
  loci,
  type = c("point", "interval"),
  boundary = c("trim", "drop")
)

Arguments

data

Quantitative input table. Metadata and mapped values are retained.

seq_data

Sequence reference table.

loci

Explicit accver, start, end and optional locus_id, as in focus_ggchord_data().

type

"point" requires pos; "interval" requires start/end.

boundary

"trim" (default) or "drop" for partly retained intervals.

Value

An ordinary data frame with focused coordinates. Its ggchord_track_focus attribute reports output-to-input rows and omitted input rows; .source_* columns retain earliest source coordinates.

See also

ggchord_data_contract

Examples

Code

library(ggchord)
library(dplyr)
data(plasmid_example_pUC19)
track_seq <- plasmid_example_pUC19 |>
  select(accver, length)
starts <- seq.int(1L, track_seq$length, by = 100L)
gc_fraction <- function(sequence) {
  bases <- strsplit(sequence, "")[[1]]
  mean(bases %in% c("G", "C"))
}
bins <- tibble(
  accver = track_seq$accver,
  start = starts,
  end = pmin(starts + 99L, track_seq$length)
) |>
  rowwise() |>
  mutate(gc = gc_fraction(substr(plasmid_example_pUC19$sequence, start, end))) |>
  ungroup()
loci <- tibble(accver = track_seq$accver, start = 501, end = 2000)
focus_ggchord_track(bins, track_seq, loci, type = "interval")