def test_rangelabel(self):
row = rangelabel.from_label("chr1:123-456", keep_gene=False)
self.assertEqual(tuple(row), ("chr1", 122, 456))
label = rangelabel.to_label(row)
self.assertEqual(label, "chr1:123-456")
# unpack_range
for region, expect in (
["chr1", ("chr1", None, None)],
["chr1:100-123", ("chr1", 99, 123)],
[("chr1", 100, 123), ("chr1", 100, 123)],
[("chr1", 100, 123, "A"), ("chr1", 100, 123)],
):
result = rangelabel.unpack_range(region)
self.assertEqual(result, expect)
def test_rangelabel(self):
row = rangelabel.from_label("chr1:123-456", keep_gene=False)
self.assertEqual(tuple(row), ("chr1", 122, 456))
label = rangelabel.to_label(row)
self.assertEqual(label, "chr1:123-456")
# unpack_range
for region, expect in (
["chr1", ("chr1", None, None)],
["chr1:100-123", ("chr1", 99, 123)],
[("chr1", 100, 123), ("chr1", 100, 123)],
[("chr1", 100, 123, "A"), ("chr1", 100, 123)],
):
result = rangelabel.unpack_range(region)
self.assertEqual(result, expect)
def translate_region_to_bins(region, bins):
"""Map genomic coordinates to bin indices.
Return a tuple of (chrom, start, end), just like unpack_range.
"""
if region is None:
return Region(None, None, None)
chrom, start, end = unpack_range(region)
if start is None and end is None:
return Region(chrom, start, end)
if start is None:
start = 0
if end is None:
end = float("inf")
# NB: only bin start positions matter here
c_bin_starts = bins.data.loc[bins.data.chromosome == chrom, "start"].values
r_start, r_end = np.searchsorted(c_bin_starts, [start, end])
return Region(chrom, r_start, r_end)
def select_range_genes(cnarr, segments, variants, show_range, show_gene,
window_width):
"""Determine which datapoints to show based on the given options.
Behaviors::
start/end show_gene
+ + given region + genes; err if any gene outside it
- + window +/- around genes
+ - given region, highlighting any genes within it
- - whole chromosome, no genes
If `show_range` is a chromosome name only, no start/end positions, then the
whole chromosome will be shown.
If region start/end coordinates are given and `show_gene` is '' or ',' (or
all commas, etc.), then instead of highlighting all genes in the selection,
no genes will be highlighted.
"""
chrom, start, end = unpack_range(show_range)
if start is None and end is None:
# Either the specified range is only chrom, no start-end, or gene names
# were given
window_coords = ()
else:
# Viewing region coordinates were specified -- take them as given
# Fill in open-ended ranges' endpoints
if start is None:
start = 0
elif start < 0:
start = 0
if not end:
# Default selection endpoint to the maximum chromosome position
end = (cnarr or segments
or variants).filter(chromosome=chrom).end.iat[-1]
if end <= start:
raise ValueError(
"Coordinate range {}:{}-{} (from {}) has size <= 0".format(
chrom, start, end, show_range))
window_coords = (start, end)
gene_ranges = []
if show_gene is None:
if window_coords:
if cnarr:
# Highlight all genes within the given range
gene_ranges = plots.gene_coords_by_range(
cnarr, chrom, start, end)[chrom]
if not gene_ranges and (end - start) < 10 * window_width:
# No genes in the selected region, so if the selection is small
# (i.e. <80% of the displayed window, <10x window padding),
# highlight the selected region itself.
# (To prevent this, use show_gene='' or window_width=0)
logging.info("No genes found in selection; will highlight the "
"selected region itself instead")
gene_ranges = [(start, end, "Selection")]
window_coords = (max(0,
start - window_width), end + window_width)
else:
gene_names = filter(None, show_gene.split(','))
if gene_names:
# Scan for probes matching the specified gene(s)
gene_coords = plots.gene_coords_by_name(cnarr or segments,
gene_names)
if len(gene_coords) > 1:
raise ValueError("Genes %s are split across chromosomes %s" %
(show_gene, list(gene_coords.keys())))
g_chrom, gene_ranges = gene_coords.popitem()
if chrom:
# Confirm that the selected chromosomes match
core.assert_equal(
"Chromosome also selected by region (-c) "
"does not match", **{
"chromosome": chrom,
"gene(s)": g_chrom
})
else:
chrom = g_chrom
gene_ranges.sort()
if window_coords:
# Verify all genes fit in the given window
for gene_start, gene_end, gene_name in gene_ranges:
if not (start <= gene_start and gene_end <= end):
raise ValueError("Selected gene %s (%s:%d-%d) "
"is outside specified region %s" %
(gene_name, chrom, gene_start,
gene_end, show_range))
elif not show_range:
# Set the display window to the selected genes +/- a margin
window_coords = (max(0, gene_ranges[0][0] - window_width),
gene_ranges[-1][1] + window_width)
# Prune plotted elements to the selected region
sel_probes = (cnarr.in_range(chrom, *window_coords) if cnarr else CNA([]))
sel_segs = (segments.in_range(chrom, *window_coords, mode='trim')
if segments else CNA([]))
sel_snvs = (variants.in_range(chrom, *window_coords) if variants else None)
logging.info(
"Showing %d probes and %d selected genes in region %s",
len(sel_probes), len(gene_ranges),
(chrom + ":%d-%d" % window_coords if window_coords else chrom))
return sel_probes, sel_segs, sel_snvs, window_coords, gene_ranges, chrom
def select_range_genes(cnarr, segments, variants, show_range, show_gene,
window_width):
"""Determine which datapoints to show based on the given options.
Behaviors::
start/end show_gene
+ + given region + genes; err if any gene outside it
- + window +/- around genes
+ - given region, highlighting any genes within it
- - whole chromosome, no genes
If `show_range` is a chromosome name only, no start/end positions, then the
whole chromosome will be shown.
If region start/end coordinates are given and `show_gene` is '' or ',' (or
all commas, etc.), then instead of highlighting all genes in the selection,
no genes will be highlighted.
"""
chrom, start, end = unpack_range(show_range)
if start is None and end is None:
# Either the specified range is only chrom, no start-end, or gene names
# were given
window_coords = ()
else:
# Viewing region coordinates were specified -- take them as given
# Fill in open-ended ranges' endpoints
if start is None:
start = 0
elif start < 0:
start = 0
if not end:
# Default selection endpoint to the maximum chromosome position
end = (cnarr or segments or variants
).filter(chromosome=chrom).end.iat[-1]
if end <= start:
raise ValueError("Coordinate range {}:{}-{} (from {}) has size <= 0"
.format(chrom, start, end, show_range))
window_coords = (start, end)
gene_ranges = []
if show_gene is None:
if window_coords:
if cnarr:
# Highlight all genes within the given range
gene_ranges = plots.gene_coords_by_range(cnarr, chrom, start, end)[chrom]
if not gene_ranges and (end - start) < 10 * window_width:
# No genes in the selected region, so if the selection is small
# (i.e. <80% of the displayed window, <10x window padding),
# highlight the selected region itself.
# (To prevent this, use show_gene='' or window_width=0)
logging.info("No genes found in selection; will highlight the "
"selected region itself instead")
gene_ranges = [(start, end, "Selection")]
window_coords = (max(0, start - window_width),
end + window_width)
else:
gene_names = filter(None, show_gene.split(','))
if gene_names:
# Scan for probes matching the specified gene(s)
gene_coords = plots.gene_coords_by_name(cnarr or segments,
gene_names)
if len(gene_coords) > 1:
raise ValueError("Genes %s are split across chromosomes %s"
% (show_gene, list(gene_coords.keys())))
g_chrom, gene_ranges = gene_coords.popitem()
if chrom:
# Confirm that the selected chromosomes match
core.assert_equal("Chromosome also selected by region (-c) "
"does not match",
**{"chromosome": chrom,
"gene(s)": g_chrom})
else:
chrom = g_chrom
gene_ranges.sort()
if window_coords:
# Verify all genes fit in the given window
for gene_start, gene_end, gene_name in gene_ranges:
if not (start <= gene_start and gene_end <= end):
raise ValueError("Selected gene %s (%s:%d-%d) "
"is outside specified region %s"
% (gene_name, chrom, gene_start,
gene_end, show_range))
elif not show_range:
# Set the display window to the selected genes +/- a margin
window_coords = (max(0, gene_ranges[0][0] - window_width),
gene_ranges[-1][1] + window_width)
# Prune plotted elements to the selected region
sel_probes = (cnarr.in_range(chrom, *window_coords)
if cnarr else CNA([]))
sel_segs = (segments.in_range(chrom, *window_coords, mode='trim')
if segments else CNA([]))
sel_snvs = (variants.in_range(chrom, *window_coords)
if variants else None)
logging.info("Showing %d probes and %d selected genes in region %s",
len(sel_probes), len(gene_ranges),
(chrom + ":%d-%d" % window_coords if window_coords else chrom))
return sel_probes, sel_segs, sel_snvs, window_coords, gene_ranges, chrom
def do_heatmap(cnarrs, show_range=None, do_desaturate=False, by_bin=False):
"""Plot copy number for multiple samples as a heatmap."""
_fig, axis = plt.subplots()
set_colorbar(axis)
# List sample names on the y-axis
axis.set_yticks([i + 0.5 for i in range(len(cnarrs))])
axis.set_yticklabels([c.sample_id for c in cnarrs])
axis.set_ylim(0, len(cnarrs))
axis.invert_yaxis()
axis.set_ylabel("Samples")
if hasattr(axis, 'set_facecolor'):
# matplotlib >= 2.0
axis.set_facecolor('#DDDDDD')
else:
# Older matplotlib
axis.set_axis_bgcolor('#DDDDDD')
if by_bin and show_range:
try:
a_cnarr = next(c for c in cnarrs if "probes" not in c)
except StopIteration:
r_chrom, r_start, r_end = unpack_range(show_range)
if r_start is not None or r_end is not None:
raise ValueError("Need at least 1 .cnr input file if --by-bin "
"(by_bin) and --chromosome (show_range) are "
"both used to specify a sub-chromosomal "
"region.")
else:
logging.info("Using sample %s to map %s to bin coordinates",
a_cnarr.sample_id, show_range)
r_chrom, r_start, r_end = plots.translate_region_to_bins(
show_range, a_cnarr)
else:
r_chrom, r_start, r_end = unpack_range(show_range)
if r_start is not None or r_end is not None:
logging.info("Showing log2 ratios in range %s:%d-%s", r_chrom, r_start
or 0, r_end or '*')
elif r_chrom:
logging.info("Showing log2 ratios on chromosome %s", r_chrom)
# Closes over do_desaturate
def cna2df(cna):
"""Extract a dataframe of plotting points from a CopyNumArray."""
points = cna.data.loc[:, ["start", "end"]]
points["color"] = cna.log2.apply(plots.cvg2rgb, args=(do_desaturate, ))
return points
# Group each file's probes/segments by chromosome
sample_data = [collections.defaultdict(list) for _c in cnarrs]
# Calculate the size (max endpoint value) of each chromosome
chrom_sizes = collections.OrderedDict()
for i, cnarr in enumerate(cnarrs):
if by_bin:
cnarr = plots.update_binwise_positions_simple(cnarr)
if r_chrom:
subcna = cnarr.in_range(r_chrom, r_start, r_end, mode="trim")
sample_data[i][r_chrom] = cna2df(subcna)
chrom_sizes[r_chrom] = max(subcna.end.iat[-1] if subcna else 0,
chrom_sizes.get(r_chrom, 0))
else:
for chrom, subcna in cnarr.by_chromosome():
sample_data[i][chrom] = cna2df(subcna)
chrom_sizes[chrom] = max(subcna.end.iat[-1] if subcna else 0,
chrom_sizes.get(r_chrom, 0))
# Closes over axis
def plot_sample_chrom(i, sample):
"""Draw the given coordinates and colors as a horizontal series."""
xranges = [(start, end - start)
for start, end in zip(sample.start, sample.end)]
bars = BrokenBarHCollection(xranges, (i, i + 1),
edgecolors="none",
facecolors=sample["color"])
axis.add_collection(bars)
if show_range:
# Lay out only the selected chromosome
# Set x-axis the chromosomal positions (in Mb), title as the selection
if by_bin:
MB = 1
axis.set_xlabel("Position (bin)")
else:
MB = plots.MB
axis.set_xlabel("Position (Mb)")
axis.set_xlim((r_start or 0) * MB,
(r_end or chrom_sizes[r_chrom]) * MB)
axis.set_title(show_range)
axis.tick_params(which='both', direction='out')
axis.get_xaxis().tick_bottom()
axis.get_yaxis().tick_left()
# Plot the individual probe/segment coverages
for i, sample in enumerate(sample_data):
crow = sample[r_chrom]
if not len(crow):
logging.warning("Sample #%d has no datapoints in selection %s",
i + 1, show_range)
crow["start"] *= MB
crow["end"] *= MB
plot_sample_chrom(i, crow)
else:
# Lay out chromosome dividers and x-axis labels
# (Just enough padding to avoid overlap with the divider line)
chrom_offsets = plots.plot_x_dividers(axis, chrom_sizes, 1)
# Plot the individual probe/segment coverages
for i, sample in enumerate(sample_data):
for chrom, curr_offset in chrom_offsets.items():
crow = sample[chrom]
if len(crow):
crow["start"] += curr_offset
crow["end"] += curr_offset
plot_sample_chrom(i, crow)
else:
logging.warning("Sample #%d has no datapoints", i + 1)
return axis
def do_heatmap(cnarrs, show_range=None, do_desaturate=False):
"""Plot copy number for multiple samples as a heatmap."""
_fig, axis = plt.subplots()
set_colorbar(axis)
# List sample names on the y-axis
axis.set_yticks([i + 0.5 for i in range(len(cnarrs))])
axis.set_yticklabels([c.sample_id for c in cnarrs])
axis.set_ylim(0, len(cnarrs))
axis.invert_yaxis()
axis.set_ylabel("Samples")
axis.set_axis_bgcolor('#DDDDDD')
r_chrom, r_start, r_end = unpack_range(show_range)
if r_start is not None or r_end is not None:
logging.info("Showing log2 ratios in range %s:%d-%s", r_chrom, r_start,
r_end or '*')
elif r_chrom:
logging.info("Showing log2 ratios on chromosome %s", r_chrom)
# Closes over do_desaturate
def cna2df(cna):
"""Extract a dataframe of plotting points from a CopyNumArray."""
points = cna.data.loc[:, ["start", "end"]]
points["color"] = cna.log2.apply(plots.cvg2rgb, args=(do_desaturate, ))
return points
# Group each file's probes/segments by chromosome
sample_data = [collections.defaultdict(list) for _c in cnarrs]
# Calculate the size (max endpoint value) of each chromosome
chrom_sizes = collections.OrderedDict()
for i, cnarr in enumerate(cnarrs):
if r_chrom:
subcna = cnarr.in_range(r_chrom, r_start, r_end, mode="trim")
sample_data[i][r_chrom] = cna2df(subcna)
chrom_sizes[r_chrom] = max(subcna.end.iat[-1] if subcna else 0,
chrom_sizes.get(r_chrom, 0))
else:
for chrom, subcna in cnarr.by_chromosome():
sample_data[i][chrom] = cna2df(subcna)
chrom_sizes[chrom] = max(subcna.end.iat[-1] if subcna else 0,
chrom_sizes.get(r_chrom, 0))
# Closes over axis
def plot_sample_chrom(i, sample):
"""Draw the given coordinates and colors as a horizontal series."""
xranges = [(start, end - start)
for start, end in zip(sample.start, sample.end)]
bars = BrokenBarHCollection(xranges, (i, i + 1),
edgecolors="none",
facecolors=sample["color"])
axis.add_collection(bars)
if show_range:
# Lay out only the selected chromosome
# Set x-axis the chromosomal positions (in Mb), title as the selection
axis.set_xlim((r_start or 0) * plots.MB,
(r_end or chrom_sizes[r_chrom]) * plots.MB)
axis.set_title(show_range)
axis.set_xlabel("Position (Mb)")
axis.tick_params(which='both', direction='out')
axis.get_xaxis().tick_bottom()
axis.get_yaxis().tick_left()
# Plot the individual probe/segment coverages
for i, sample in enumerate(sample_data):
crow = sample[r_chrom]
crow["start"] *= plots.MB
crow["end"] *= plots.MB
plot_sample_chrom(i, crow)
else:
# Lay out chromosome dividers and x-axis labels
# (Just enough padding to avoid overlap with the divider line)
chrom_offsets = plots.plot_x_dividers(axis, chrom_sizes, 1)
# Plot the individual probe/segment coverages
for i, sample in enumerate(sample_data):
for chrom, curr_offset in chrom_offsets.items():
crow = sample[chrom]
if len(crow):
crow["start"] += curr_offset
crow["end"] += curr_offset
plot_sample_chrom(i, crow)
return axis
def do_heatmap(cnarrs, show_range=None, do_desaturate=False, by_bin=False):
"""Plot copy number for multiple samples as a heatmap."""
_fig, axis = plt.subplots()
set_colorbar(axis)
# List sample names on the y-axis
axis.set_yticks([i + 0.5 for i in range(len(cnarrs))])
axis.set_yticklabels([c.sample_id for c in cnarrs])
axis.set_ylim(0, len(cnarrs))
axis.invert_yaxis()
axis.set_ylabel("Samples")
if hasattr(axis, 'set_facecolor'):
# matplotlib >= 2.0
axis.set_facecolor('#DDDDDD')
else:
# Older matplotlib
axis.set_axis_bgcolor('#DDDDDD')
if by_bin and show_range:
try:
a_cnarr = next(c for c in cnarrs if "probes" not in c)
except StopIteration:
r_chrom, r_start, r_end = unpack_range(show_range)
if r_start is not None or r_end is not None:
raise ValueError("Need at least 1 .cnr input file if --by-bin "
"(by_bin) and --chromosome (show_range) are "
"both used to specify a sub-chromosomal "
"region.")
else:
logging.info("Using sample %s to map %s to bin coordinates",
a_cnarr.sample_id, show_range)
r_chrom, r_start, r_end = plots.translate_region_to_bins(show_range,
a_cnarr)
else:
r_chrom, r_start, r_end = unpack_range(show_range)
if r_start is not None or r_end is not None:
logging.info("Showing log2 ratios in range %s:%d-%s",
r_chrom, r_start or 0, r_end or '*')
elif r_chrom:
logging.info("Showing log2 ratios on chromosome %s", r_chrom)
# Closes over do_desaturate
def cna2df(cna):
"""Extract a dataframe of plotting points from a CopyNumArray."""
points = cna.data.loc[:, ["start", "end"]]
points["color"] = cna.log2.apply(plots.cvg2rgb, args=(do_desaturate,))
return points
# Group each file's probes/segments by chromosome
sample_data = [collections.defaultdict(list) for _c in cnarrs]
# Calculate the size (max endpoint value) of each chromosome
chrom_sizes = collections.OrderedDict()
for i, cnarr in enumerate(cnarrs):
if by_bin:
cnarr = plots.update_binwise_positions_simple(cnarr)
if r_chrom:
subcna = cnarr.in_range(r_chrom, r_start, r_end, mode="trim")
sample_data[i][r_chrom] = cna2df(subcna)
chrom_sizes[r_chrom] = max(subcna.end.iat[-1] if subcna else 0,
chrom_sizes.get(r_chrom, 0))
else:
for chrom, subcna in cnarr.by_chromosome():
sample_data[i][chrom] = cna2df(subcna)
chrom_sizes[chrom] = max(subcna.end.iat[-1] if subcna else 0,
chrom_sizes.get(r_chrom, 0))
# Closes over axis
def plot_sample_chrom(i, sample):
"""Draw the given coordinates and colors as a horizontal series."""
xranges = [(start, end - start)
for start, end in zip(sample.start, sample.end)]
bars = BrokenBarHCollection(xranges, (i, i+1),
edgecolors="none",
facecolors=sample["color"])
axis.add_collection(bars)
if show_range:
# Lay out only the selected chromosome
# Set x-axis the chromosomal positions (in Mb), title as the selection
if by_bin:
MB = 1
axis.set_xlabel("Position (bin)")
else:
MB = plots.MB
axis.set_xlabel("Position (Mb)")
axis.set_xlim((r_start or 0) * MB,
(r_end or chrom_sizes[r_chrom]) * MB)
axis.set_title(show_range)
axis.tick_params(which='both', direction='out')
axis.get_xaxis().tick_bottom()
axis.get_yaxis().tick_left()
# Plot the individual probe/segment coverages
for i, sample in enumerate(sample_data):
crow = sample[r_chrom]
if not len(crow):
logging.warning("Sample #%d has no datapoints in selection %s",
i+1, show_range)
crow["start"] *= MB
crow["end"] *= MB
plot_sample_chrom(i, crow)
else:
# Lay out chromosome dividers and x-axis labels
# (Just enough padding to avoid overlap with the divider line)
chrom_offsets = plots.plot_x_dividers(axis, chrom_sizes, 1)
# Plot the individual probe/segment coverages
for i, sample in enumerate(sample_data):
for chrom, curr_offset in chrom_offsets.items():
crow = sample[chrom]
if len(crow):
crow["start"] += curr_offset
crow["end"] += curr_offset
plot_sample_chrom(i, crow)
else:
logging.warning("Sample #%d has no datapoints", i+1)
return axis
def chromosome_scatter(cnarr, segments, variants, show_range, show_gene,
antitarget_marker, do_trend, window_width, y_min, y_max,
title, segment_color):
"""Plot a specified region on one chromosome.
Possibilities::
Options | Shown
------------ | --------
-c | -g | Genes | Region
------- | -- | ----- | ------
- | + | given | auto: gene(s) + margin
chr | - | none | whole chrom
chr | + | given | whole chrom
chr:s-e | - | all | given
chr:s-e | + | given | given
"""
chrom, start, end = unpack_range(show_range)
window_coords = ()
genes = []
if show_gene:
gene_names = show_gene.split(',')
# Scan for probes matching the specified gene
gene_coords = plots.gene_coords_by_name(cnarr or segments, gene_names)
if len(gene_coords) != 1:
raise ValueError("Genes %s are split across chromosomes %s" %
(show_gene, list(gene_coords.keys())))
g_chrom, genes = gene_coords.popitem()
if chrom:
# Confirm that the selected chromosomes match
core.assert_equal(
"Chromosome also selected by region (-c) "
"does not match", **{
"chromosome": chrom,
"gene(s)": g_chrom
})
else:
chrom = g_chrom
# Set the display window to the selected genes +/- a margin
genes.sort()
window_coords = (max(0, genes[0][0] - window_width),
genes[-1][1] + window_width)
if start is not None or end is not None:
# Default selection endpoint to the maximum chromosome position
if not end:
end = (cnarr or segments
or variants).filter(chromosome=chrom).end.iat[-1]
if window_coords:
# Genes were specified, & window was set around them
if start > window_coords[0] or end < window_coords[1]:
raise ValueError("Selected gene region " + chrom +
(":%d-%d" % window_coords) +
" is outside specified region " + show_range)
window_coords = (max(0, start - window_width), end + window_width)
if cnarr and not genes:
genes = plots.gene_coords_by_range(cnarr, chrom, start, end)[chrom]
if not genes and window_width > (end - start) / 10.0:
# No genes in the selected region, so highlight the region
# itself (unless the selection is ~entire displayed window)
logging.info("No genes found in selection; will show the "
"selected region itself instead")
genes = [(start, end, "Selection")]
elif show_range and window_coords:
# Specified range is only chrom, no start-end
# Reset window around selected genes to show the whole chromosome
window_coords = ()
# Prune plotted elements to the selected region
sel_probes = (cnarr.in_range(chrom, *window_coords) if cnarr else CNA([]))
sel_seg = (segments.in_range(chrom, *window_coords, mode='trim')
if segments else CNA([]))
sel_snvs = (variants.in_range(chrom, *window_coords) if variants else None)
logging.info(
"Showing %d probes and %d selected genes in region %s",
len(sel_probes), len(genes),
(chrom + ":%d-%d" % window_coords if window_coords else chrom))
# Create plots
if cnarr or segments:
# Plot CNVs at chromosome level
if variants:
# Lay out top 3/5 for the CN scatter, bottom 2/5 for SNP plot
axgrid = pyplot.GridSpec(5, 1, hspace=.5)
axis = pyplot.subplot(axgrid[:3])
axis2 = pyplot.subplot(axgrid[3:], sharex=axis)
# Plot allele freqs for only the selected region
snv_on_chromosome(axis2, sel_snvs, sel_seg, genes, do_trend)
else:
_fig, axis = pyplot.subplots()
axis.set_xlabel("Position (Mb)")
cnv_on_chromosome(axis,
sel_probes,
sel_seg,
genes,
antitarget_marker=antitarget_marker,
do_trend=do_trend,
x_limits=window_coords,
y_min=y_min,
y_max=y_max,
segment_color=segment_color)
elif variants:
# Only plot SNVs in a single-panel layout
_fig, axis = pyplot.subplots()
snv_on_chromosome(axis, sel_snvs, sel_seg, genes, do_trend)
if title is None:
title = "%s %s" % ((cnarr or segments or variants).sample_id, chrom)
axis.set_title(title)
