High-Level Wrappers: Copy Number, Hi-C, and ChIP

SeqPlotR ships a small family of wrapper functions that assemble common genomic visualisations from the primitive elements. Each wrapper returns a seq_plot that can be further composed with %+%, %|%, %__%, or [seq_resolve()].

library(SeqPlotR)
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library(GenomicRanges)
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seq_copynumber()

Single-sample CN scatter coloured by integer state, with optional segmentation overlay.

win <- GRanges(c("chr1", "chr2"), IRanges(c(1, 1), c(1e6, 1.5e6)))

cn_gr <- GRanges(
  rep(c("chr1", "chr2"), each = 150),
  IRanges(start = c(sample(1:1e6, 150), sample(1:1.5e6, 150)), width = 5000),
  cn        = sample(0:5, 300, replace = TRUE,
                     prob = c(.05, .1, .55, .15, .1, .05)),
  log2ratio = rnorm(300, 0, 0.3)
)

seg <- GRanges(c("chr1", "chr2"),
               IRanges(c(1, 1), c(1e6, 1.5e6)),
               seg_mean = c(0.0, -0.3))

p <- seq_copynumber(cn_gr, windows = win,
                    segment_data = seg, segment_col = "seg_mean")
p$plot()
#> 5 out-of-bounds data points excluded! (seq_segment)
#> 5 out-of-bounds data points excluded! (seq_segment)

Column detection is automatic — cn_col falls back through c("cn", "copy_number", "CN", "state", "integer_cn") and ratio_col through c("log2ratio", "logR", "log2R", "ratio", "log2_ratio").

seq_cn_heatmap()

Multi-sample CN heatmap — one row per sample, tiles coloured by CN state.

samples <- paste0("S", 1:5)
cnh_gr  <- GRanges(
  rep(c("chr1", "chr2"), each = 300),
  IRanges(start = c(sample(1:1e6, 300, replace = TRUE),
                    sample(1:1.5e6, 300, replace = TRUE)), width = 5000),
  sample = sample(samples, 600, replace = TRUE),
  cn     = sample(0:5, 600, replace = TRUE)
)

p <- seq_cn_heatmap(cnh_gr, windows = win,
                    sample_col = "sample", cn_col = "cn",
                    sample_order = samples)
p$plot()

seq_hic() — four styles

One call to seq_hic() produces one style. Combine styles via seq_resolve() for side-by-side panels.

style = "triangle"

seq_hic(hic_gr, windows = win1, style = "triangle")$plot()

style = "rectangle"

Caps the distance axis at max_dist:

seq_hic(hic_gr, windows = win1, style = "rectangle", max_dist = 3e5)$plot()

style = "full" and "diagonal"

The full contact matrix lives on a 2D genomic grid:

seq_hic(hic_gr, windows = win1, style = "full")$plot()

seq_chip()

ChIP-style signal + peak tracks. data is either a named list of GRanges (one per sample) or a single GRanges with a sample column.

make_sig <- function(nm) {
  g <- GRanges("chr1",
               IRanges(sort(sample(1:1e6, 400)), width = 500),
               score = rexp(400, rate = 0.15))
  S4Vectors::mcols(g)$sample <- nm
  g
}
sig <- list(Rad21 = make_sig("Rad21"), NippedB = make_sig("NippedB"))
peaks <- list(Rad21   = GRanges("chr1", IRanges(sort(sample(1:1e6, 20)), width = 2000)),
              NippedB = GRanges("chr1", IRanges(sort(sample(1:1e6, 15)), width = 2000)))

p <- seq_chip(sig, peaks = peaks,
              windows = GRanges("chr1", IRanges(1, 1e6)))
p$plot()

Composing wrappers with seq_resolve()

seq_resolve() is the key plumbing function for combining wrapper plots — it extracts each child’s tracks and appends them to a parent seq_plot under the requested direction.

win1 <- GRanges("chr1", IRanges(1, 1e6))

cn1 <- seq_copynumber(cn_gr[seqnames(cn_gr) == "chr1"],
                      windows = win1, track_id = "CN1")
hic <- seq_hic(hic_gr, windows = win1, style = "triangle",
               track_id = "HiC")

fig <- seq_resolve(seq_plot(), cn1, hic)
fig$plot()
#> 5 out-of-bounds data points excluded! (seq_segment)

#> Warning in .merge_two_Seqinfo_objects(x, y): The 2 combined objects have no sequence levels in common. (Use
#>   suppressWarnings() to suppress this warning.)

Pass unique track_id values to each wrapper call to avoid ID collisions when resolving multiple plots into one figure.