def _get_plot_view_configs(self):
"""
Any change to the 'raw' view of a report plot should be changed here.
There's three histogram plots.
1. Subread concordance
2. Subread rendlength
3. Readlength
"""
_p = [
PlotViewProperties(
Constants.P_SUBREAD_CONCORDANCE,
Constants.PG_SUBREAD_CONCORDANCE,
generate_plot,
'mapped_subread_concordance_histogram.png',
xlabel=get_plot_xlabel(spec, Constants.PG_SUBREAD_CONCORDANCE,
Constants.P_SUBREAD_CONCORDANCE),
ylabel=get_plot_ylabel(spec, Constants.PG_SUBREAD_CONCORDANCE,
Constants.P_SUBREAD_CONCORDANCE),
color=get_green(3),
edgecolor=get_green(2),
use_group_thumb=True,
plot_group_title=get_plot_title(
spec,
Constants.PG_SUBREAD_CONCORDANCE,
Constants.P_SUBREAD_CONCORDANCE)),
PlotViewProperties(
Constants.P_SUBREAD_LENGTH,
Constants.PG_SUBREAD_LENGTH,
generate_plot,
'mapped_subreadlength_histogram.png',
xlabel=get_plot_xlabel(spec, Constants.PG_SUBREAD_LENGTH,
Constants.P_SUBREAD_LENGTH),
ylabel=get_plot_ylabel(spec, Constants.PG_SUBREAD_LENGTH,
Constants.P_SUBREAD_LENGTH),
use_group_thumb=True,
color=get_blue(3),
edgecolor=get_blue(2),
plot_group_title=get_plot_title(spec,
Constants.PG_SUBREAD_LENGTH,
Constants.P_SUBREAD_LENGTH)),
PlotViewProperties(
Constants.P_READLENGTH,
Constants.PG_READLENGTH,
generate_plot,
'mapped_readlength_histogram.png',
xlabel=get_plot_xlabel(spec, Constants.PG_READLENGTH,
Constants.P_READLENGTH),
ylabel=get_plot_ylabel(spec, Constants.PG_READLENGTH,
Constants.P_READLENGTH),
color=get_blue(3),
edgecolor=get_blue(2),
use_group_thumb=True,
plot_group_title=get_plot_title(spec, Constants.PG_READLENGTH,
Constants.P_READLENGTH)),
]
return {v.plot_id: v for v in _p}
def _get_plot_view_configs(self):
"""
Any change to the 'raw' view of a report plot should be changed here.
There's three histogram plots.
1. Subread concordance
2. Subread rendlength
3. Readlength
"""
_p = [
PlotViewProperties(
Constants.P_SUBREAD_CONCORDANCE,
Constants.PG_SUBREAD_CONCORDANCE,
generate_plot,
'mapped_subread_concordance_histogram.png',
xlabel=get_plot_xlabel(spec, Constants.PG_SUBREAD_CONCORDANCE,
Constants.P_SUBREAD_CONCORDANCE),
ylabel=get_plot_ylabel(spec, Constants.PG_SUBREAD_CONCORDANCE,
Constants.P_SUBREAD_CONCORDANCE),
color=get_green(3),
edgecolor=get_green(2),
use_group_thumb=True,
plot_group_title=get_plot_title(
spec,
Constants.PG_SUBREAD_CONCORDANCE,
Constants.P_SUBREAD_CONCORDANCE)),
PlotViewProperties(
Constants.P_SUBREAD_LENGTH,
Constants.PG_SUBREAD_LENGTH,
generate_plot,
'mapped_subreadlength_histogram.png',
xlabel=get_plot_xlabel(spec, Constants.PG_SUBREAD_LENGTH,
Constants.P_SUBREAD_LENGTH),
ylabel=get_plot_ylabel(spec, Constants.PG_SUBREAD_LENGTH,
Constants.P_SUBREAD_LENGTH),
use_group_thumb=True,
color=get_blue(3),
edgecolor=get_blue(2),
plot_group_title=get_plot_title(spec,
Constants.PG_SUBREAD_LENGTH,
Constants.P_SUBREAD_LENGTH)),
PlotViewProperties(
Constants.P_READLENGTH,
Constants.PG_READLENGTH,
generate_plot,
'mapped_readlength_histogram.png',
xlabel=get_plot_xlabel(spec, Constants.PG_READLENGTH,
Constants.P_READLENGTH),
ylabel=get_plot_ylabel(spec, Constants.PG_READLENGTH,
Constants.P_READLENGTH),
color=get_blue(3),
edgecolor=get_blue(2),
use_group_thumb=True,
plot_group_title=get_plot_title(spec, Constants.PG_READLENGTH,
Constants.P_READLENGTH)),
]
return {v.plot_id: v for v in _p}
def _plot_view_configs():
"""
Any change to the 'raw' view of a report plot should be changed here.
"""
_p = [PlotViewProperties(Constants.P_PRE_FILTER_READ_LENGTH_HIST,
Constants.PG_READ_LENGTH,
custom_read_length_histogram,
Constants.I_PRE_FILTER_READ_LENGTH,
xlabel="ReadLength",
ylabel="Reads",
rlabel="bp > Read Length",
title="Pre-Filter",
color=get_green(3),
edgecolor=get_green(2),
plot_group_title="Polymerase Read Length"),
PlotViewProperties(Constants.P_POST_FILTER_READ_LENGHT_HIST,
Constants.PG_READ_LENGTH,
custom_read_length_histogram,
Constants.I_POST_FILTER_READ_LENGTH,
xlabel="ReadLength",
ylabel="Reads",
rlabel="bp > Read Length",
title="Post-Filter",
color=get_green(3),
edgecolor=get_green(2),
use_group_thumb=True,
plot_group_title="Polymerase Read Length"),
PlotViewProperties(Constants.P_PRE_FILTER_READ_SCORE_HIST,
Constants.PG_READ_SCORE,
custom_read_accuracy_histogram,
Constants.I_PRE_FILTER_READ_SCORE,
xlabel="Read Quality",
ylabel="Reads",
rlabel="bp > Read Quality",
title="Pre-Filter",
color=get_blue(3),
edgecolor=get_blue(2),
plot_group_title="Polymerase Read Quality"),
PlotViewProperties(Constants.P_POST_FILTER_READ_SCORE_HIST,
Constants.PG_READ_SCORE,
custom_read_accuracy_histogram,
Constants.I_POST_FILTER_READ_SCORE,
xlabel="Read Quality",
ylabel="Reads",
rlabel="bp > Read Quality",
title="Post-Filter",
color=get_blue(3),
edgecolor=get_blue(2),
use_group_thumb=True,
plot_group_title="Polymerase Read Quality")
]
# make it easier to access
return {v.plot_id: v for v in _p}
def _get_plot_view_configs(self):
"""
Any change to the 'raw' view of a report plot should be changed here.
There's three histogram plots.
1. Subread accuracy
2. Subread rendlength
3. Readlength
"""
_p = [
PlotViewProperties(
Constants.P_SUBREAD_ACCURACY,
Constants.PG_SUBREAD_ACCURACY,
generate_plot,
'mapped_subread_accuracy_histogram.png',
xlabel="Concordance",
ylabel="Subreads",
color=get_green(3),
edgecolor=get_green(2),
use_group_thumb=True,
plot_group_title="Mapped Subread Accuracy"),
PlotViewProperties(
Constants.P_SUBREAD_LENGTH,
Constants.PG_SUBREAD_LENGTH,
generate_plot,
'mapped_subreadlength_histogram.png',
xlabel="Subread Length",
ylabel="Subreads",
use_group_thumb=True,
color=get_blue(3),
edgecolor=get_blue(2),
plot_group_title="Mapped Subread Length"),
PlotViewProperties(
Constants.P_READLENGTH,
Constants.PG_READLENGTH,
generate_plot,
'mapped_readlength_histogram.png',
xlabel="Read Length",
ylabel="Reads",
color=get_blue(3),
edgecolor=get_blue(2),
use_group_thumb=True,
plot_group_title="Mapped Polymerase Read Length")
]
return {v.plot_id: v for v in _p}
def make_nreads_histogram(bc_groups, base_dir):
"""
Create simple histogram of read count frequency per barcode.
"""
fig, ax = make_histogram(
datum=[float(g.n_reads) for g in bc_groups], # FIXME workaround
axis_labels=["Number of Reads", "Number of Barcoded Samples"],
nbins=min(len(bc_groups), 20),
barcolor=get_blue(3))
return _to_plot(fig, Constants.P_HIST_NREADS, base_dir)
def make_readlength_histogram(bc_groups, base_dir):
"""
Create simple histogram of read length frequency per barcode.
"""
fig, ax = make_histogram(
datum=[float(g.mean_read_length()) for g in bc_groups], # FIXME
axis_labels=["Mean Read Length", "Number of Barcoded Samples"],
nbins=min(len(bc_groups), 20),
barcolor=get_blue(3))
return _to_plot(fig, Constants.P_HIST_RL, base_dir)
def _create_bars(contig_variants):
"""
:param contig_variants: (ContigVariants)
:returns: tuple of pbreports.plot.helper.Bar objects
"""
dataIns = np.array([l[1] for l in contig_variants.variants])
dataDels = np.array([l[2] for l in contig_variants.variants])
dataSnv = np.array([l[3] for l in contig_variants.variants])
insBarModel = PH.Bar(dataIns, 'Insertions', color=PH.get_blue(3))
delBarModel = PH.Bar(dataDels, 'Deletions', color=PH.get_green(3))
snvBarModel = PH.Bar(dataSnv, 'Substitutions', color=PH.get_orange())
return (insBarModel, delBarModel, snvBarModel)
def make_bcqual_histogram(bc_groups, base_dir):
"""
Create simple histogram of barcode quality score frequency over all
barcoded subreads.
"""
data = []
for g in bc_groups:
data.extend(g.bqs)
fig, ax = make_histogram(
datum=data,
axis_labels=["Barcode Quality Score", "Number of Barcoded Subreads"],
nbins=50,
barcolor=get_blue(3))
ax.axvline(26, color='r')
return _to_plot(fig, Constants.P_HIST_BQ, base_dir)
_custom_read_accuracy_histogram = functools.partial(
_custom_histogram_with_cdf,
meta_rpt.get_meta_plotgroup(Constants.PG_ACCURACY).get_meta_plot(
Constants.P_ACCURACY).ylabel["Custom"], 1000000)
# These functions need to generate a function with signature (data,
# output_dir, dpi=)
create_readlength_plot = functools.partial(
create_plot, _custom_read_length_histogram, Constants.P_READLENGTH,
(meta_rpt.get_meta_plotgroup(Constants.PG_READLENGTH).get_meta_plot(
Constants.P_READLENGTH).xlabel,
meta_rpt.get_meta_plotgroup(Constants.PG_READLENGTH).get_meta_plot(
Constants.P_READLENGTH).ylabel["L"],
meta_rpt.get_meta_plotgroup(Constants.PG_READLENGTH).get_meta_plot(
Constants.P_READLENGTH).ylabel["R"]), 80,
Constants.I_CCS_READ_LENGTH_HIST, get_blue(3))
create_accuracy_plot = functools.partial(
create_plot, _custom_read_accuracy_histogram, Constants.P_ACCURACY,
(meta_rpt.get_meta_plotgroup(Constants.PG_ACCURACY).get_meta_plot(
Constants.P_ACCURACY).xlabel,
meta_rpt.get_meta_plotgroup(Constants.PG_ACCURACY).get_meta_plot(
Constants.P_ACCURACY).ylabel["L"],
meta_rpt.get_meta_plotgroup(Constants.PG_ACCURACY).get_meta_plot(
Constants.P_ACCURACY).ylabel["R"]), 80,
Constants.I_CCS_READ_ACCURACY_HIST, get_green(3))
create_npasses_plot = functools.partial(
create_plot, _make_histogram, Constants.P_NPASSES,
(meta_rpt.get_meta_plotgroup(Constants.PG_NPASSES).get_meta_plot(
Constants.P_NPASSES).xlabel,
fig.savefig(path, dpi=dpi)
log.debug("Saved plot with id {i} to {p}".format(p=path, i=plot_id))
thumbnail = plot_name.replace(".png", "_thumb.png")
fig.savefig(os.path.join(output_dir, thumbnail), dpi=20)
plt.close(fig)
log.debug("Saved plot to {p}".format(p=thumbnail))
plot = Plot(plot_id, os.path.basename(plot_name),
thumbnail=os.path.basename(thumbnail))
return plot
create_readlength_plot = functools.partial(
__create_plot, _make_histogram_with_cdf, Constants.P_READLENGTH,
("Read Length", "Reads", "Reads > Read Length"), 80,
"consensus_isoforms_readlength_hist.png", get_blue(3))
def makeReport(inReadsFN, inSummaryFN, outDir):
"""
Generate a report with ID, tables, attributes and plot groups.
inReadsFN --- an input FASTA file which has all consensus
isoforms produced by pbtranscript.py cluster.
This file is required to plot a read length histogram as part of
the report:
consensus_isoforms_readlength_hist.png
inSummaryFN --- a summary TXT file with cluster attributes,
including two attributes:
number of consensus isoforms
log.debug("Saved plot to {p}".format(p=thumbnail))
plot = Plot(plot_id, to_b(plot_name), thumbnail=to_b(thumbnail))
return plot
# These functions create signatures (datum, axis_labels, nbins, barcolor
_custom_read_length_histogram = functools.partial(
_custom_histogram_with_cdf, "Mb > Read Length", 1000000)
_custom_read_accuracy_histogram = functools.partial(
_custom_histogram_with_cdf, "Mb > Predicted Accuracy", 1000000)
# These functions need to generate a function with signature (datum,
# output_dir, dpi=)
create_readlength_plot = functools.partial(__create_plot, _custom_read_length_histogram, Constants.P_READLENGTH,
("Read Length", "Reads", "bp > Read Length"), 80, Constants.I_CCS_READ_LENGTH_HIST, get_blue(3))
create_accuracy_plot = functools.partial(__create_plot, _custom_read_accuracy_histogram, Constants.P_ACCURACY,
("Quality", "Reads", "bp > Predicted Accuracy"), 80, Constants.I_CCS_READ_ACCURACY_HIST, get_green(3))
create_npasses_plot = functools.partial(__create_plot, _make_histogram, Constants.P_NPASSES,
("Number of Passes", "Reads"), 80, Constants.I_CCS_NUM_PASSES_HIST, "#F18B17")
create_scatter_plot = functools.partial(__create_plot,
scatter_plot_accuracy_vs_numpasses, Constants.P_SCATTER,
("Number of passes",
"Predicted accuracy (Phred QV)"), None,
Constants.I_CCS_SCATTER_PLOT, get_blue(3))
def to_report(ccs_subread_set, output_dir):
fig.savefig(path, dpi=dpi)
log.debug("Saved plot with id {i} to {p}".format(p=path, i=plot_id))
thumbnail = plot_name.replace(".png", "_thumb.png")
fig.savefig(os.path.join(output_dir, thumbnail), dpi=20)
plt.close(fig)
log.debug("Saved plot to {p}".format(p=thumbnail))
plot = Plot(plot_id, os.path.basename(plot_name),
thumbnail=os.path.basename(thumbnail))
return plot
create_readlength_plot = functools.partial(
__create_plot, _make_histogram_with_cdf, Constants.P_READLENGTH,
("Read Length", "Reads", "Reads > Read Length"), 80,
"consensus_isoforms_readlength_hist.png", get_blue(3))
create_avgqv_plot = functools.partial(
__create_plot, _make_histogram_with_cdf, Constants.P_AVGQV,
("HQ LQ Isoform Average QV", "Isoforms", "Isoforms > Average QV"), 80,
"hq_lq_isoforms_avgqv_hist.png", get_blue(3))
def makeReport(inReadsFN, hq_isoforms_fq, lq_isoforms_fq, inSummaryFN, outDir):
"""
Generate a report with ID, tables, attributes and plot groups.
inReadsFN --- an input FASTA file which has all consensus
isoforms produced by pbtranscript.py cluster.
This file is required to plot a read length histogram as part of
the report:
fig.savefig(path, dpi=dpi)
log.debug("Saved plot with id {i} to {p}".format(p=path, i=plot_id))
thumbnail = plot_name.replace(".png", "_thumb.png")
fig.savefig(os.path.join(output_dir, thumbnail), dpi=20)
plt.close(fig)
log.debug("Saved plot to {p}".format(p=thumbnail))
plot = Plot(plot_id, os.path.basename(plot_name),
thumbnail=os.path.basename(thumbnail))
return plot
create_readlength_plot = functools.partial(
__create_plot, _make_histogram_with_cdf, Constants.P_READLENGTH,
("Read Length", "Reads", "Reads > Read Length"),
80, "fulllength_nonchimeric_readlength_hist.png", get_blue(3))
def make_report(contig_set, summary_txt, output_dir):
"""
Generate a report with ID, tables, attributes and plot groups.
:param contig_set: an input FASTA file which has all full-length,
non-chimeric reads produced by pbtranscript.py classify.
This file is required to plot a read length histogram as part of
the report:
fulllength_nonchimeric_readlength_hist.png
:param summary_txt: a summary TXT file with classify attributes,
including 6 attributes,
thumbnail = plot_name.replace(".png", "_thumb.png")
fig.savefig(os.path.join(output_dir, thumbnail), dpi=20)
plt.close(fig)
log.debug("Saved plot to {p}".format(p=thumbnail))
plot = Plot(plot_id,
os.path.basename(plot_name),
thumbnail=os.path.basename(thumbnail))
return plot
create_readlength_plot = functools.partial(
__create_plot, _make_histogram_with_cdf, Constants.P_READLENGTH,
("Read Length", "Reads", "Reads > Read Length"), 80,
"consensus_isoforms_readlength_hist.png", get_blue(3))
create_avgqv_plot = functools.partial(
__create_plot, _make_histogram_with_cdf, Constants.P_AVGQV,
("HQ LQ Isoform Average QV", "Isoforms", "Isoforms > Average QV"), 80,
"hq_lq_isoforms_avgqv_hist.png", get_blue(3))
def makeReport(inReadsFN, hq_isoforms_fq, lq_isoforms_fq, inSummaryFN, outDir):
"""
Generate a report with ID, tables, attributes and plot groups.
inReadsFN --- an input FASTA file which has all consensus
isoforms produced by pbtranscript.py cluster.
This file is required to plot a read length histogram as part of
the report:
# These functions create signatures (data, axis_labels, nbins, barcolor
_custom_read_length_histogram = functools.partial(_custom_histogram_with_cdf, "Mb > Read Length", 1000000)
_custom_read_accuracy_histogram = functools.partial(_custom_histogram_with_cdf, "Mb > Read Score", 1000000)
# These functions need to generate a function with signature (data,
# output_dir, dpi=)
create_readlength_plot = functools.partial(
create_plot,
_custom_read_length_histogram,
Constants.P_READLENGTH,
(get_plot_xlabel(spec, Constants.PG_READLENGTH, Constants.P_READLENGTH), "Reads", "bp > Read Length"),
80,
Constants.I_CCS_READ_LENGTH_HIST,
get_blue(3),
)
create_accuracy_plot = functools.partial(
create_plot,
_custom_read_accuracy_histogram,
Constants.P_ACCURACY,
(get_plot_xlabel(spec, Constants.PG_ACCURACY, Constants.P_ACCURACY), "Reads", "bp > Read Score"),
80,
Constants.I_CCS_READ_ACCURACY_HIST,
get_green(3),
)
create_npasses_plot = functools.partial(
create_plot,
_make_histogram,
# These functions create signatures (data, axis_labels, nbins, barcolor)
_custom_read_length_histogram = functools.partial(_custom_histogram_with_cdf,
"Mb > Read Length", 1000000)
# FIXME the fallback label is incorrect!
_custom_read_accuracy_histogram = functools.partial(_custom_histogram_with_cdf,
"Mb > Read Score",
sys.maxint)
# These functions need to generate a function with signature (data,
# output_dir, dpi=)
create_readlength_plot = functools.partial(
create_plot, _custom_read_length_histogram, Constants.P_READLENGTH,
(get_plot_xlabel(spec, Constants.PG_READLENGTH,
Constants.P_READLENGTH), "Reads", "bp > Read Length"), 50,
Constants.I_CCS_READ_LENGTH_HIST, get_blue(3))
create_accuracy_plot = functools.partial(
create_plot, _custom_read_accuracy_histogram, Constants.P_ACCURACY,
(get_plot_xlabel(spec, Constants.PG_ACCURACY,
Constants.P_ACCURACY), "Reads", "reads > Read Score"),
100, Constants.I_CCS_READ_ACCURACY_HIST, get_green(3))
create_npasses_plot = functools.partial(
create_plot, make_histogram, Constants.P_NPASSES,
(get_plot_xlabel(spec, Constants.PG_NPASSES, Constants.P_NPASSES),
get_plot_ylabel(spec, Constants.PG_NPASSES, Constants.P_NPASSES)), 80,
Constants.I_CCS_NUM_PASSES_HIST, "#F18B17")
create_scatter_plot = functools.partial(
create_plot, scatter_plot_accuracy_vs_numpasses, Constants.P_SCATTER,
# PlotGroup
PG_READLENGTH = "fulllength_nonchimeric_readlength_group"
# Plots
P_READLENGTH = "fulllength_nonchimeric_readlength_hist"
# Table
T_ATTR = "isoseq_classify_table"
spec = load_spec(Constants.R_ID)
create_readlength_plot = functools.partial(
create_plot_impl, make_histogram_with_cdf, Constants.P_READLENGTH,
("Read Length", "Reads", "Reads > Read Length"), 80,
"fulllength_nonchimeric_readlength_hist.png", get_blue(3))
def make_report(contig_set, summary_txt, output_dir):
"""
Generate a report with ID, tables, attributes and plot groups.
:param contig_set: an input FASTA file which has all full-length,
non-chimeric reads produced by pbtranscript.py classify.
This file is required to plot a read length histogram as part of
the report:
fulllength_nonchimeric_readlength_hist.png
:param summary_txt: a summary TXT file with classify attributes,
including 6 attributes,
return plot
# These functions create signatures (data, axis_labels, nbins, barcolor
_custom_read_length_histogram = functools.partial(
_custom_histogram_with_cdf, "Mb > Read Length", 1000000)
_custom_read_accuracy_histogram = functools.partial(
_custom_histogram_with_cdf, "Mb > Read Score", 1000000)
# These functions need to generate a function with signature (data,
# output_dir, dpi=)
create_readlength_plot = functools.partial(
create_plot, _custom_read_length_histogram, Constants.P_READLENGTH,
(get_plot_xlabel(spec, Constants.PG_READLENGTH, Constants.P_READLENGTH),
"Reads", "bp > Read Length"),
80, Constants.I_CCS_READ_LENGTH_HIST, get_blue(3))
create_accuracy_plot = functools.partial(
create_plot, _custom_read_accuracy_histogram, Constants.P_ACCURACY,
(get_plot_xlabel(spec, Constants.PG_ACCURACY, Constants.P_ACCURACY),
"Reads", "bp > Read Score"),
80, Constants.I_CCS_READ_ACCURACY_HIST, get_green(3))
create_npasses_plot = functools.partial(
create_plot, _make_histogram, Constants.P_NPASSES,
(get_plot_xlabel(spec, Constants.PG_NPASSES, Constants.P_NPASSES),
get_plot_ylabel(spec, Constants.PG_NPASSES, Constants.P_NPASSES)),
80, Constants.I_CCS_NUM_PASSES_HIST, "#F18B17")
create_scatter_plot = functools.partial(
create_plot, scatter_plot_accuracy_vs_numpasses, Constants.P_SCATTER,
fig.savefig(os.path.join(output_dir, thumbnail), dpi=20)
plt.close(fig)
log.debug("Saved plot to {p}".format(p=thumbnail))
plot = Plot(plot_id, os.path.basename(plot_name),
thumbnail=os.path.basename(thumbnail))
return plot
create_readlength_plot = functools.partial(
__create_plot, _make_histogram_with_cdf, Constants.P_READLENGTH,
(meta_rpt.get_meta_plotgroup(Constants.PG_READLENGTH).get_meta_plot(Constants.P_READLENGTH).xlabel,
meta_rpt.get_meta_plotgroup(Constants.PG_READLENGTH).get_meta_plot(Constants.P_READLENGTH).ylabel["L"],
meta_rpt.get_meta_plotgroup(Constants.PG_READLENGTH).get_meta_plot(Constants.P_READLENGTH).ylabel["R"]),
80,
"consensus_isoforms_readlength_hist.png", get_blue(3))
def makeReport(inReadsFN, inSummaryFN, outDir):
"""
Generate a report with ID, tables, attributes and plot groups.
inReadsFN --- an input FASTA file which has all consensus
isoforms produced by pbtranscript.py cluster.
This file is required to plot a read length histogram as part of
the report:
consensus_isoforms_readlength_hist.png
inSummaryFN --- a summary TXT file with cluster attributes,
including two attributes:
number of consensus isoforms