Sashimi-style coverage plot for a splice event
Source:R/generics.R, R/visualization.R
PlotSashimi.RdDraws junction arcs scaled by read count over a schematic gene structure. Arcs are coloured by role: inclusion (blue) vs exclusion (red). Works in both junction mode and transcript mode. Optionally faceted by a cell metadata column.
Draws junction arcs scaled by aggregate read count over a schematic gene structure. Arcs are coloured by role: inclusion (blue) vs exclusion (red).
Usage
PlotSashimi(
object,
event_id,
cells = NULL,
group_by = NULL,
arc_scale = c("sqrt", "linear", "log"),
colours = c(inclusion = "#4393c3", exclusion = "#d6604d"),
title = NULL,
...
)
# S4 method for class 'MatisseObject'
PlotSashimi(
object,
event_id,
cells = NULL,
group_by = NULL,
arc_scale = c("sqrt", "linear", "log"),
colours = c(inclusion = "#4393c3", exclusion = "#d6604d"),
title = NULL,
...
)Arguments
- object
A
MatisseObjectwith a PSI assay computed.- event_id
Character. A single event ID. Run
rownames(GetSeurat(obj)[["psi"]])to list available IDs; typical SE format is"SE:chr1:1201-2999:3201-4999:+".- cells
Character vector of cell barcodes to aggregate over. Default: all cells.
- group_by
Character. Column in Seurat meta.data to facet by. Default:
NULL(all cells pooled).- arc_scale
Character. How to scale arc height to read count:
"sqrt"(default),"linear", or"log".- colours
Named character vector with elements
"inclusion"and"exclusion"giving arc colours.- title
Character. Plot title. Defaults to
event_id.- ...
Additional arguments (see
PlotSashimi).
Details
In junction mode each arc corresponds to an individual junction
with its own read count. In transcript mode the SE event_id is
parsed to derive junction coordinates; inclusion and exclusion counts come
from the "counts" and "exclusion" layers of the PSI assay.
Supported event types in transcript mode: every SUPPA2 type Matisse ingests – SE (skipped exon), RI (retained intron), A3/A5 (alternative 3'/5' splice site), AF/ AL (alternative first/last exon), and MX (mutually exclusive exons). Junction coordinates for the SUPPA2 grammar are parsed with the same logic as the short-read junction adapter. Junction mode supports all event types since coordinates are auto-parsed from junction IDs.
Note on transcript-mode multi-arc events: transcript-level counting aggregates reads to events, not to individual junctions. When an event side has more than one defining junction (the two SE / MX inclusion arcs, the two MX exclusion arcs), the total event count for that side is split evenly across its arcs. The arcs may have differed in reality; use junction-mode input if you need per-junction read counts.