Plot frequency of Tn5 insertion events for different groups of cells within given regions of the genome. Tracks are normalized using a per-group scaling factor computed as the number of cells in the group multiplied by the mean sequencing depth for that group of cells. This accounts for differences in number of cells and potential differences in sequencing depth between groups.
CoveragePlot(
object,
region,
features = NULL,
assay = NULL,
split.assays = FALSE,
assay.scale = "common",
show.bulk = FALSE,
expression.assay = "RNA",
expression.slot = "data",
annotation = TRUE,
peaks = TRUE,
peaks.group.by = NULL,
ranges = NULL,
ranges.group.by = NULL,
ranges.title = "Ranges",
region.highlight = NULL,
links = TRUE,
tile = FALSE,
tile.size = 100,
tile.cells = 100,
bigwig = NULL,
bigwig.type = "coverage",
bigwig.scale = "common",
heights = NULL,
group.by = NULL,
split.by = NULL,
window = 100,
extend.upstream = 0,
extend.downstream = 0,
scale.factor = NULL,
ymax = NULL,
cells = NULL,
idents = NULL,
sep = c("-", "-"),
max.downsample = 3000,
downsample.rate = 0.1,
...
)Returns a patchwork object
A Seurat object
A set of genomic coordinates to show. Can be a GRanges object, a string encoding a genomic position, a gene name, or a vector of strings describing the genomic coordinates or gene names to plot. If a gene name is supplied, annotations must be present in the assay.
A vector of features present in another assay to plot alongside accessibility tracks (for example, gene names).
Name of the assay to plot. If a list of assays is provided, data from each assay will be shown overlaid on each track. The first assay in the list will define the assay used for gene annotations, links, and peaks (if shown). The order of assays given defines the plotting order.
When plotting data from multiple assays, display each assay as a separate track. If FALSE, data from different assays are overlaid on a single track with transparancy applied.
Scaling to apply to data from different assays. Can be:
common: plot all assays on a common scale (default)
separate: plot each assay on a separate scale ranging from zero to the maximum value for that assay within the plotted region
Include coverage track for all cells combined (pseudo-bulk). Note that this will plot the combined accessibility for all cells included in the plot (rather than all cells in the object).
Name of the assay containing expression data to plot
alongside accessibility tracks. Only needed if supplying features
argument.
Name of slot to pull expression data from. Only needed
if supplying the features argument.
Display gene annotations. Set to TRUE or FALSE to control whether genes models are displayed, or choose "transcript" to display all transcript isoforms, or "gene" to display gene models only (same as setting TRUE).
Display peaks
Grouping variable to color peaks by. Must be a variable present in the feature metadata. If NULL, do not color peaks by any variable.
Additional genomic ranges to plot
Grouping variable to color ranges by. Must be a
variable present in the metadata stored in the ranges genomic ranges.
If NULL, do not color by any variable.
Y-axis title for ranges track. Only relevant if
ranges parameter is set.
Region to highlight on the plot. Should be a GRanges object containing the coordinates to highlight. By default, regions will be highlighted in grey. To change the color of the highlighting, include a metadata column in the GRanges object named "color" containing the color to use for each region.
Display links
Display per-cell fragment information in sliding windows. If plotting multi-assay data, only the first assay is shown in the tile plot.
Size of the sliding window for per-cell fragment tile plot
Number of cells to display fragment information for in tile plot.
List of bigWig file paths to plot data from. Files can be remotely hosted. The name of each element in the list will determine the y-axis label given to the track.
Type of track to use for bigWig files ("line", "heatmap", or "coverage"). Should either be a single value, or a list of values giving the type for each individual track in the provided list of bigwig files.
Same as assay.scale parameter, except for bigWig
files when plotted with bigwig.type="coverage"
Relative heights for each track (accessibility, gene annotations, peaks, links).
Name of one or more metadata columns to group (color) the cells by. Default is the current cell identities
A metadata variable to split the tracks by. For example, grouping by "celltype" and splitting by "batch" will create separate tracks for each combination of celltype and batch.
Smoothing window size
Number of bases to extend the region upstream.
Number of bases to extend the region downstream.
Scaling factor for track height. If NULL (default), use the median group scaling factor determined by total number of fragments sequences in each group.
Maximum value for Y axis. Can be one of:
NULL: set to the highest value among all the tracks (default)
qXX: clip the maximum value to the XX quantile (for example, q95 will set the maximum value to 95% of the maximum value in the data). This can help remove the effect of extreme values that may otherwise distort the scale.
numeric: manually define a Y-axis limit
Which cells to plot. Default all cells
Which identities to include in the plot. Default is all identities.
Separators to use for strings encoding genomic coordinates. First element is used to separate the chromosome from the coordinates, second element is used to separate the start from end coordinate.
Minimum number of positions kept when downsampling. Downsampling rate is adaptive to the window size, but this parameter will set the minimum possible number of positions to include so that plots do not become too sparse when the window size is small.
Fraction of positions to retain when downsampling. Retaining more positions can give a higher-resolution plot but can make the number of points large, resulting in larger file sizes when saving the plot and a longer period of time needed to draw the plot.
Additional arguments passed to wrap_plots
Additional information can be layered on the coverage plot by setting several different options in the CoveragePlot function. This includes showing:
gene annotations
peak positions
additional genomic ranges
additional data stored in a bigWig file, which may be hosted remotely
gene or protein expression data alongside coverage tracks
peak-gene links
the position of individual sequenced fragments as a heatmap
data for multiple chromatin assays simultaneously
a pseudobulk for all cells combined
# \donttest{
fpath <- system.file("extdata", "fragments.tsv.gz", package="Signac")
fragments <- CreateFragmentObject(
path = fpath,
cells = colnames(atac_small),
validate.fragments = FALSE
)
Fragments(atac_small) <- fragments
# Basic coverage plot
CoveragePlot(object = atac_small, region = c("chr1-713500-714500"))
# Show additional ranges
ranges.show <- StringToGRanges("chr1-713750-714000")
CoveragePlot(object = atac_small, region = c("chr1-713500-714500"), ranges = ranges.show)
# Highlight region
CoveragePlot(object = atac_small, region = c("chr1-713500-714500"), region.highlight = ranges.show)
# Change highlight color
ranges.show$color <- "orange"
CoveragePlot(object = atac_small, region = c("chr1-713500-714500"), region.highlight = ranges.show)
# Show expression data
CoveragePlot(object = atac_small, region = c("chr1-713500-714500"), features = "ELK1")
# }
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