wspace=0.05,
top=0.8,
bottom=0)
f2_ax3 = fig2.add_subplot(spec2[0, 0])
f2_ax4 = fig2.add_subplot(spec2[1, 0])
cuts_colorbar_ax = fig2.add_subplot(spec1[0, 0])
# add gene model
properties_dict = {
'file': 'test.bed',
'color': 'grey',
'labels': 'on',
'style': 'UCSC',
'fontsize': 9
}
bed = tracks.BedTrack(properties_dict)
# axis 1 is the project
# axis 2 is the tss enrichment
# axis 3 is the heatmap
# axis 4 is the gene model
cut_norm = mcolors.Normalize(vmin=0, vmax=heatmap.max().max())
f2_ax3.imshow(heatmap,
aspect='auto',
cmap=newcmp,
extent=(heatmap.columns.min(), heatmap.columns.max(), 0, 1),
norm=cut_norm)
f2_ax3.set_xlim(START, END)
f2_ax3.xaxis.set_ticklabels('')
f2_ax3.yaxis.set_ticklabels('')
track_config = dict(file=GENCODE_BED,
arrow_length=1000,
arrow_interval=10,
file_type='bed',
height=3,
color='black',
merge_transcripts=False,
labels=True,
section_name='',
prefered_name='gene_name',
global_max_row=False,
font_size=8,
style="UCSC",
all_labels_inside=False,
labels_in_margin=True)
tk = pygtk.BedTrack(track_config)
# In[3]:
#track_config = dict(file='/lab/data/reference/human/hg19/annot/gencode.v19.annotation.gtf.gz', file_type='bed', height=3, color='black', line_width=0.1, merge_transcripts=False, labels=True, section_name='', prefered_name='gene_name', global_max_row=False, font_size=8, style="UCSC", all_labels_inside=False, labels_in_margin=True)
#tk = pygtk.BedTrack(track_config)
# In[30]:
CLUSTER_NAMES = '/lab/work/porchard/sn-muscle-project/cluster-names.txt'
cluster_names = pd.read_csv(CLUSTER_NAMES, sep='\t').astype(str)
cluster_colors = cmap_utils.make_colormap_dict(
cluster_names.new_name.to_list())
cluster_names = dict(zip(cluster_names.old_name, cluster_names.new_name))
# In[51]:
def plot_tracks(region, track_configs, outfig_name, **kwargs):
if len(track_configs) < 2:
raise Exception(
"Invalid track numbers... We only accepted more than one track right now..."
)
figsize = kwargs.get("figsize", (16, 9))
fig, axs = plt.subplots(len(track_configs),
1,
sharex='col',
figsize=figsize)
plt.subplots_adjust(left=0.1, right=0.8, bottom=0.1, top=0.9)
for i in range(0, len(track_configs)):
ax = axs[i]
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)
infile_type = track_configs[i]['file'].split(".")[-1]
if infile_type == 'cool':
if track_configs[i].get('section_name') is None:
track_configs[i]['section_name'] = 'HiC'
if track_configs[i].get('region') is None:
track_configs[i]['region'] = "{}:{}-{}".format(
region[0], region[1], region[2])
tk = pygtk.HiCMatrixTrack(track_configs[i])
tk.plot(ax, region[0],
int(region[1]) + track_configs[i]['depth'],
int(region[2]) - track_configs[i]['depth'])
ax.set_yticks([])
axins = inset_axes(ax,
width="1%",
height="100%",
loc='lower left',
bbox_to_anchor=(0, 0, 1, 1),
bbox_transform=ax.transAxes,
borderpad=0)
cobar = fig.colorbar(tk.img, ax=ax, cax=axins)
cobar.ax.yaxis.set_ticks_position('left')
if tk.properties.get('title') is not None:
draw_track_title(ax, tk.properties['title'])
if infile_type == 'arcs' or infile_type == 'links':
if track_configs[i].get('section_name') is None:
track_configs[i]['section_name'] = 'Links'
elif track_configs[i].get('section_name') == 'clusters':
if track_configs[i].get('color') is None \
or not is_colormap(track_configs[i].get('color')):
track_configs[i]['color'] = default_colormap
if track_configs[i].get('clusters') is None:
tmp_pd = pd.read_csv(track_configs[i].get('file'),
sep="\t",
header=None)
track_configs[i]['min_value'] = 1
track_configs[i]['max_value'] = tmp_pd.iloc[:, 6].max()
n_clusters = track_configs[i]['max_value'] - track_configs[
i]['min_value'] + 1
else:
track_configs[i]['min_value'] = 1
track_configs[i]['max_value'] = track_configs[i].get(
'clusters')
n_clusters = track_configs[i].get('clusters')
tk = pygtk.LinksTrack(track_configs[i])
tk.plot(ax, region[0], region[1], region[2])
ax.set_yticks([])
axins = inset_axes(ax,
width="1%",
height="100%",
loc='lower left',
bbox_to_anchor=(0, 0, 1, 1),
bbox_transform=ax.transAxes,
borderpad=0)
if tk.properties.get('section_name') == 'clusters':
ticks = np.linspace(tk.properties.get('min_value'),
tk.properties.get('max_value'), n_clusters)
bounds = np.append((ticks - 0.5),
(tk.properties.get('max_value') + 0.5))
cobar = fig.colorbar(tk.colormap,
ax=ax,
cax=axins,
ticks=ticks,
boundaries=bounds)
else:
cobar = fig.colorbar(tk.colormap, ax=ax, cax=axins)
cobar.ax.yaxis.set_ticks_position('left')
if tk.properties.get('title') is not None:
draw_track_title(ax, tk.properties['title'])
if infile_type == 'bigwig' or infile_type == 'bw':
if track_configs[i].get('section_name') is None:
track_configs[i]['section_name'] = 'BigWig'
tk = pygtk.BigWigTrack(track_configs[i])
tk.plot(ax, region[0], region[1], region[2])
if tk.properties.get('title') is not None:
draw_track_title(ax, tk.properties['title'])
if infile_type == 'gtf':
if track_configs[i].get('section_name') is None:
track_configs[i]['section_name'] = 'Gene'
tk = pygtk.GtfTrack(track_configs[i])
tk.plot(ax, region[0], region[1], region[2])
ax.set_yticks([])
if tk.properties.get('title') is not None:
draw_track_title(ax, tk.properties['title'])
if infile_type == 'bed':
if track_configs[i].get('section_name') is None:
track_configs[i]['section_name'] = 'Bed'
elif track_configs[i].get('section_name') == 'clusters':
if track_configs[i].get('color') is None \
or not is_colormap(track_configs[i].get('color')):
track_configs[i]['color'] = default_colormap
if track_configs[i].get('clusters') is None:
tmp_pd = pd.read_csv(track_configs[i].get('file'),
sep="\t",
header=None)
track_configs[i]['min_value'] = 1
track_configs[i]['max_value'] = tmp_pd.iloc[:, 4].max()
n_clusters = track_configs[i]['max_value'] - track_configs[
i]['min_value'] + 1
else:
track_configs[i]['min_value'] = 1
track_configs[i]['max_value'] = track_configs[i].get(
'clusters')
n_clusters = track_configs[i].get('clusters')
tk = pygtk.BedTrack(track_configs[i])
tk.plot(ax, region[0], region[1], region[2])
ax.set_yticks([])
if is_colormap(tk.properties['color']):
axins = inset_axes(
ax,
width="1%", # width = 1% of parent_bbox width
height="100%", # height : 100%
loc='lower left',
bbox_to_anchor=(0, 0, 1, 1),
bbox_transform=ax.transAxes,
borderpad=0)
if tk.properties.get('section_name') == 'clusters':
ticks = np.linspace(tk.properties.get('min_value'),
tk.properties.get('max_value'),
n_clusters)
bounds = np.append((ticks - 0.5),
(tk.properties.get('max_value') + 0.5))
cobar = fig.colorbar(tk.colormap,
ax=ax,
cax=axins,
ticks=ticks,
boundaries=bounds)
else:
cobar = fig.colorbar(tk.colormap, ax=ax, cax=axins)
cobar.ax.yaxis.set_ticks_position('left')
if tk.properties.get('title') is not None:
draw_track_title(ax, tk.properties['title'])
plt.savefig(outfig_name)