stackJunctions: Stack the y-axis position of junctions

In jmw86069/splicejam: Analysis and Visualization of Gene Splice Variants and Transcriptome Data

Stack the y-axis position of junctions

Description

Stack the y-axis position of junctions

Usage

stackJunctions(
  gr,
  scoreColname = "score",
  sampleColname = "sample_id",
  scoreFactor = 1,
  matchFrom = NULL,
  matchTo = NULL,
  strandedScore = TRUE,
  baseline = NULL,
  verbose = FALSE,
  ...
)

Arguments

gr	GRanges object representing splice junctions.
scoreColname	character string matching one of colnames(GenomicRanges::values(gr)) that contains a numeric value representing the abundance of each splice junction observed.
sampleColname	character string with the column or columns that contain biological sample identifier, used to ensure junctions are only stacked within a sample, and not across samples. When sampleColname is NULL, all junctions are stacked.
scoreFactor	numeric value multiplied by the value in scoreColname to allow scaling the junctions across samples. Note that scoreFactor can be a vector, which would be applied to the vector of scores.
matchFrom, matchTo	optional colnames to use when grouping junctions at the start and end positions. By default "nameFrom" and "nameTo" are used, as output from closestExonToJunctions(), which has the benefit of grouping junctions within the spliceBuffer distance from exon boundaries. If those values are not present colnames(GenomicRanges::values(gr)) then the new default c("seqnames", "start", "strand") is used for matchFrom, and c("seqnames", "end", "strand") is used for matchTo. That said, if matchFrom or matchTo are supplied, those colnames are used from as.data.frame(gr). Multiple colnames are allowed. Note also that sampleColname is appended to matchFrom and matchTo to ensure that matching is only performed within each sampleColname value.
strandedScore	logical indicating whether to enforce negative scores for junctions on the "-" strand. Note that when strandedScore is true, all "-" strand scores will be negative, and all other scores with be positive.
baseline	numeric vector of length 0, 1 or length(gr), with values added to the y-axis value for junctions. If baseline has names matching names(gr) they will be used for each gr entry; if baseline is not named, values are recycled to length(gr). The purpose is to allow exons to be shifted up or down on the y-axis, along with associated junctions and coverage data (see exoncov2polygon() for another example.)
verbose	logical indicating whether to print verbose output.
...	additional arguments are ignored.

Details

This function is intended to help visualize splice junctions specifically when plotted using geom_diagonal_wide_arc(), where the height of the junction arc is defined by the score. When two junctions have the same start position, their y-positions are stacked, such that the shorter junction width is placed before longer junction widths. The intention is to reduce visible overlaps.

The input data is expected to have annotations similar to those provided by closestExonToJunctions(), specifically the columns "nameFrom" and "nameTo", see examples below. When the input data does not contain columns "nameFrom" and and "nameTo", the junctions are by default stacked by coordinates.

Value

GRanges with colnames c("yStart", "yEnd") added to values(gr), indicating the baseline y-axis position for the start and end of the junction arc. The score values(gr)[[scoreColname]] will reflect the adjustments by scoreFactor, and if strandedScore=TRUE then all strand "-" scores will be negative, all other scores will be positive.

See Also

Other jam plot functions: bgaPlotly3d(), factor2label(), gene2gg(), grl2df(), jitter_norm(), plotSashimi(), prepareSashimi()

Other jam GRanges functions: addGRLgaps(), addGRgaps(), annotateGRLfromGRL(), annotateGRfromGR(), assignGRLexonNames(), closestExonToJunctions(), combineGRcoverage(), exoncov2polygon(), findOverlapsGRL(), flattenExonsBy(), getFirstStrandedFromGRL(), getGRLgaps(), getGRcoverageFromBw(), getGRgaps(), grl2df(), jam_isDisjoint(), make_ref2compressed(), sortGRL(), spliceGR2junctionDF()

Examples

library(GenomicRanges);
library(ggplot2);
library(ggforce);
library(colorjam);
library(jamba);
grExons <- GRanges(seqnames=rep("chr1", 4),
   ranges=IRanges::IRanges(
      start=c(100, 300, 500,  900),
        end=c(200, 400, 750, 1000)),
   strand=rep("+", 4));
names(grExons) <- jamba::makeNames(rep("exon", length(grExons)),
   suffix="");

grJunc <- GRanges(seqnames=rep("chr1", 6),
   ranges=IRanges::IRanges(start=c(200, 200, 400, 400, 750, 750),
      end=c(300, 500, 500, 900, 900, 1200)),
   strand=rep("+", 6),
   score=c(200, 50, 160, 40, 210, 10));
names(grJunc) <- jamba::makeNames(rep("junc", length(grJunc)));

# quick plot showing exons and junctions using rectangles
grl <- c(
   GenomicRanges::GRangesList(exons=grExons),
   split(grJunc, names(grJunc))
   );
ggplot(grl2df(grl), aes(x=x, y=y, group=id, fill=feature_type)) +
   ggforce::geom_shape() +
   scale_y_continuous(breaks=seq_along(grl)-1, labels=names(grl)) +
   colorjam::theme_jam() +
   colorjam::scale_fill_jam() +
   ggtitle("Schematic of exons and junctions GRanges");

# add annotation for closest known exon
grJunc <- closestExonToJunctions(grJunc, grExons, spliceBuffer=5)$spliceGRgene;

# The un-stacked junctions
grlJunc2df1 <- grl2df(grJunc,
   shape="junction",
   doStackJunctions=FALSE);
ggplot(grlJunc2df1, aes(x=x, y=y, group=gr_name, fill=gr_name)) +
   geom_diagonal_wide_arc(alpha=0.7) +
   colorjam::scale_fill_jam() +
   colorjam::theme_jam() +
   ggtitle("Junctions not stacked at boundaries")

# The stacked junctions
grJunc2 <- stackJunctions(grJunc);
grlJunc2df2 <- grl2df(grJunc2,
   scoreArcMinimum=20,
   shape="junction");
ggplot(grlJunc2df2, aes(x=x, y=y, group=gr_name, fill=gr_name)) +
   geom_diagonal_wide_arc(alpha=0.7) +
   colorjam::scale_fill_jam() +
   colorjam::theme_jam() +
   ggtitle("Junctions stacked at boundaries");

## Another view showing the junction_rank
## based upon max reads entering and exiting each exon edge
ggplot(grlJunc2df2, aes(x=x, y=y, group=gr_name)) +
   geom_diagonal_wide_arc(aes(alpha=junction_rank), fill="orange") +
   scale_alpha_manual(values=c(`1`=0.4, `2`=0.6, `3`=0.7)) +
   colorjam::scale_fill_jam() +
   colorjam::theme_jam() +
   ggtitle("Junctions stacked at boundaries")

## Last example showing how two samples are kept separate
grJunc_samples <- c(grJunc, grJunc);
values(grJunc_samples)[,"sample_id"] <- rep(c("SampleA","SampleB"),
   each=length(grJunc));
names(grJunc_samples) <- jamba::makeNames(GenomicRanges::values(grJunc_samples)[,"sample_id"]);
grlJunc2df_samples <- grl2df(grJunc_samples,
   scoreArcMinimum=20,
   shape="junction");
ggplot(grlJunc2df_samples, aes(x=x, y=y, group=gr_name, fill=gr_name)) +
   geom_diagonal_wide_arc(alpha=0.7,
      show.legend=FALSE) +
   colorjam::scale_fill_jam() +
   colorjam::theme_jam() +
   ggtitle("Junctions stacked at boundaries") +
   facet_wrap(~sample_id)

jmw86069/splicejam documentation built on Nov. 4, 2024, 10:53 a.m.