def test_cropping():
features = [
GraphicFeature(start=5,
end=20,
strand=+1,
color="#ffd700",
label="Small feature"),
GraphicFeature(
start=20,
end=500,
strand=+1,
color="#ffcccc",
label="Gene 1 with a very long name",
),
GraphicFeature(start=400,
end=700,
strand=-1,
color="#cffccc",
label="Gene 2"),
GraphicFeature(start=600,
end=900,
strand=+1,
color="#ccccff",
label="Gene 3"),
]
# PLOT AND EXPORT A LINEAR VIEW OF THE CONSTRUCT
record = GraphicRecord(sequence_length=1000, features=features)
cropped_record = record.crop((425, 650))
assert len(cropped_record.features) == 3
def test_cropping_on_the_edge():
repeated_sequence = "ATGCATGCAT"
graphic_record = GraphicRecord(
sequence_length=1000, sequence=100 * repeated_sequence
)
small_gr = graphic_record.crop((990, 1000))
assert small_gr.sequence == repeated_sequence
def create_dna_structure(file_name):
results = request.get_json()
features = []
for i, spacerRepeat in enumerate(results['spacerRepeats']):
features.append(GraphicFeature(start=spacerRepeat['position'], end=spacerRepeat['position']+len(spacerRepeat['repeat']),
strand=+1, color="#cffccc", label="Repeat_"+str(i+1)))
if 'spacer' in spacerRepeat:
features.append(GraphicFeature(start=spacerRepeat['position']+len(spacerRepeat['repeat'])+1,
end=spacerRepeat['position']+len(spacerRepeat['repeat'])+spacerRepeat['lengths'][1], strand=+1, color="#ccccff",
label="Spacer_"+str(i+1)))
record = GraphicRecord(sequence_length=results['length'], features=features)
record = record.crop((results['spacerRepeats'][0]['position']-50,
results['spacerRepeats'][len(results['spacerRepeats'])-1]['position']+
len(results['spacerRepeats'][len(results['spacerRepeats'])-1]['repeat'])+50))
ax, _ = record.plot(figure_width=10)
ax.figure.savefig('static/logos/'+str(file_name)+'.png', bbox_inches='tight')
return jsonify('{"success":1}')
strand=+1,
color="#ffcccc",
label="Gene 1 with a very long name"),
GraphicFeature(start=400,
end=700,
strand=-1,
color="#cffccc",
label="Gene 2"),
GraphicFeature(start=600,
end=900,
strand=+1,
color="#ccccff",
label="Gene 3")
])
zoom_start, zoom_end = 398, 428 # coordinates of the "detail"
cropped_record = record.crop((zoom_start, zoom_end))
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 3))
# PLOT THE WHOLE SEQUENCE
ax1.set_title("Whole sequence", loc='left', weight='bold')
record.plot(ax=ax1)
ax1.fill_between((zoom_start, zoom_end), +1000, -1000, alpha=0.15)
# PLOT THE SEQUENCE DETAILS
cropped_record.plot(ax=ax2)
cropped_record.plot_sequence(ax=ax2)
cropped_record.plot_translation(ax=ax2,
location=(408, 423),
def show_crispr_grna_results(
sequence: str,
guides: List[dict],
indexes: Optional[List[int]] = None,
scoreField: str = "onTargetScore",
):
"""Shows guide rnas results for CRISPR.
Args:
sequence (str): A string containing the complete organism sequence
guides (dict): A table on 'records' format that contains guides info.\
The required fields are `start` (int), `end` (ind), indicating the limits of the guide in sequence's index.
indexes(list): Indexes (start and end) of the targeted sequence within the complete sequence. \
If not set, the targeting sequence is not shown.
scoreField (str): Select which score from GRNA tool show in the chart. \
Available scores are "onTargetScore" (default) and "offTargetScore"
"""
targeting_seq_feat = []
# Show main targeted sequence if index are set. If not, we calculate indexes to limit plot range at the `crop`
# instruction.
if indexes is not None:
targeting_seq_feat = [
GraphicFeature(
start=indexes[0],
end=indexes[1],
color="#cffccc",
label="Sequence",
strand=+1,
),
]
else:
# TODO(diegovalenzuelaiturra): Check behavior is the same when using generators instead of lists.
# indexes = [min([x['start'] for x in guides]), max([x['end'] for x in guides])]
indexes = [
min(x['start'] for x in guides),
max(x['end'] for x in guides)
]
# Plot records
record = GraphicRecord(
sequence=sequence,
features=targeting_seq_feat + [
GraphicFeature(
start=x['start'],
end=x['end'] + 1,
color="#ffcccc",
label=f"{scoreField}: {x[scoreField]}",
strand=+1 if x['forward'] else -1,
) for x in guides
],
)
# Limit plot range
record = record.crop((indexes[0] - 10, indexes[1] + 11)) # crop
# Plot and set to show sequence
ax, _ = record.plot(figure_width=20)
record.plot_sequence(ax)
