def load_random_chromosome(chr_name):
"""Generate a chromosome with random information about it.
"""
cur_chromosome = BasicChromosome.Chromosome(chr_name)
num_segments = random.randrange(num_possible_segments)
for seg in range(num_segments):
# make the top and bottom telomeres
if seg == 0:
cur_segment = BasicChromosome.TelomereSegment()
elif seg == num_segments - 1:
cur_segment = BasicChromosome.TelomereSegment(1)
# otherwise, they are just regular segments
else:
cur_segment = BasicChromosome.ChromosomeSegment()
color_chance = random.random()
if color_chance <= color_prob:
fill_color = random.choice(color_choices)
cur_segment.fill_color = fill_color
id_chance = random.random()
if id_chance <= id_prob:
id = get_random_id()
cur_segment.label = id
cur_chromosome.add(cur_segment)
return cur_chromosome, num_segments
def draw_chromosome(sequence):
entries = [("Legionella Pneumophilia")]
max_len = 30432563
telomere_length = 1000000
chr_diagram = BasicChromosome.Organism()
chr_diagram.page_size = (29.7*cm, 21*cm) #A4 landscape
for name, length in entries:
cur_chromosome = BasicChromosome.Chromosome(name)
cur_chromosome.scale_num = max_len + 2 * telomere_length
start = BasicChromosome.TelomereSegment()
start.scale = telomere_length
cur_chromosome.add(start)
body = BasicChromosome.ChromosomeSegment()
body.scale = length
cur_chromosome.add(body)
end = BasicChromosome.TelomereSegement(inverted=True)
end.scale = telomere_length
cur_chromosome.add(end)
chr_diagram.add(cur_chromosome)
chr_diagram.draw("Chromosome.pdf", "Legionella Pneumophilia")
def drawchrom(cvsfile, write_func, *args):
"""Draw CE chromosome tool.
Doesn't need any parameters.
"""
from Bio.Graphics import BasicChromosome
from reportlab.lib.colors import gray, black
entries = [("chrI", 15072419), ("chrII", 15279316), ("chrIII", 13783681),
("chrIV", 17493784), ("chrV", 20919398), ("chrX", 17718852)]
max_length = max([x[1] for x in entries])
chr_diagram = BasicChromosome.Organism()
for name, length in entries:
cur_chromosome = BasicChromosome.Chromosome(name)
#Set the length, adding and extra 20 percent for the tolomeres:
cur_chromosome.scale_num = max_length * 1.1
# Add an opening telomere
start = BasicChromosome.TelomereSegment()
start.scale = 0.05 * max_length
start.fill_color = black
cur_chromosome.add(start)
#Add a body - using bp as the scale length here.
body = BasicChromosome.ChromosomeSegment()
body.fill_color = gray
body.scale = length
cur_chromosome.add(body)
#Add a closing telomere
end = BasicChromosome.TelomereSegment(inverted=True)
end.scale = 0.05 * max_length
end.fill_color = black
cur_chromosome.add(end)
#This chromosome is done
chr_diagram.add(cur_chromosome)
chr_diagram.draw("simple_chrom.pdf", "Caenorhabditis elegans")
def load_chromosome(chr_name):
"""Load a chromosome and all of its segments.
"""
cur_chromosome = BasicChromosome.Chromosome(chr_name)
chr_segment_info = all_chr_info[chr_name]
for seg_info_num in range(len(chr_segment_info)):
label, fill_color, scale = chr_segment_info[seg_info_num]
# make the top and bottom telomeres
if seg_info_num == 0:
cur_segment = BasicChromosome.TelomereSegment()
elif seg_info_num == len(chr_segment_info) - 1:
cur_segment = BasicChromosome.TelomereSegment(1)
# otherwise, they are just regular segments
else:
cur_segment = BasicChromosome.ChromosomeSegment()
if label != "":
cur_segment.label = label
if fill_color is not None:
cur_segment.fill_color = fill_color
cur_segment.scale = scale
cur_chromosome.add(cur_segment)
# scale by the size of chromosome 2
cur_chromosome.scale_num = 19
return cur_chromosome
def plot_chr(featDict, acceptedSeqs, karyotypeDict, telomereDict, maxLen, plotWidth, plotHeight, plotTitle, outFile):
# initialise karyotype plot variables
telomere_length = 25e4
chr_diagram = BasicChromosome.Organism()
chr_diagram.page_size = (plotWidth*cm, plotHeight*cm)
for seqname in acceptedSeqs:
length = karyotypeDict[seqname]
cur_chromosome = BasicChromosome.Chromosome(seqname)
# Set the scale to the MAXIMUM length plus the two telomeres in bp
cur_chromosome.scale_num = maxLen + 2 * telomere_length
# Add an opening telomere
if seqname + "L" in telomereDict.keys():
start = BasicChromosome.TelomereSegment()
start.scale = telomere_length
cur_chromosome.add(start)
# Add a body - again using bp as the scale length here.
body = BasicChromosome.AnnotatedChromosomeSegment(
length, featDict[seqname])
body.scale = length
cur_chromosome.add(body)
# Add a closing telomere
if seqname + "R" in telomereDict.keys():
end = BasicChromosome.TelomereSegment(inverted=True)
end.scale = telomere_length
cur_chromosome.add(end)
# This chromosome is done
chr_diagram.add(cur_chromosome)
chr_diagram.draw(outFile, plotTitle)
def drawSNPLoc(vcffile, faifile, PageSize=(40*cm, 20*cm), \
outfile="location_of_SNP.pdf", Title=None, \
LabelCol=None, telomere_length=None ):
chromlen = get_chromlen(faifile)
get_gbfile(chromlen, vcffile)
#set telomere_length
max_len = max([i for i in chromlen.values()])
if not telomere_length: telomere_length = int(max_len / 20)
#get entries ( example: entries = [("Chr I", "test.gb")] )
gbfilename = os.listdir('gbfile')
entries = [(i.split('.')[0], os.path.join('gbfile',i)) \
for i in gbfilename if i.endswith('.gb')]
#draw start
#step1: draw the background of your picture
chr_diagram = BasicChromosome.Organism()
chr_diagram.page_size = PageSize
#step2: draw chromsomes in background
for index, (name, filename) in enumerate(entries):
record = SeqIO.read(filename, "genbank")
length = len(record)
features = [f for f in record.features if f.type == "tRNA"]
if not LabelCol:
#Draw colorful labels
for f in features:
f.qualifiers["color"] = [index + 2]
else:
#Draw color you set
for f in features:
f.qualifiers["color"] = [LabelCol]
cur_chromosome = BasicChromosome.Chromosome(name)
#Set the scale to the MAXIMUM length plus the two telomeres in bp
cur_chromosome.scale_num = max_len + 2 * telomere_length
#Add an opening telomere
start = BasicChromosome.TelomereSegment()
start.scale = telomere_length
cur_chromosome.add(start)
#Add a body - again using bp as the scale length here.
body = BasicChromosome.AnnotatedChromosomeSegment(length, features)
body.scale = length
cur_chromosome.add(body)
#Add a closing telomere
end = BasicChromosome.TelomereSegment(inverted=True)
end.scale = telomere_length
cur_chromosome.add(end)
#This chromosome is done
chr_diagram.add(cur_chromosome)
chr_diagram.draw(outfile, Title)
shutil.rmtree('gbfile')
def test_widget(self):
"""Try widget derived functionality.
"""
test_widget = BasicChromosome.ChromosomeSegment()
expected_string = "chr_percent = 0.25"
# trick to write the properties to a string
save_stdout = sys.stdout
new_stdout = StringIO()
sys.stdout = new_stdout
test_widget.dumpProperties()
properties = new_stdout.getvalue()
sys.stdout = save_stdout
self.assertTrue(
expected_string in properties,
"Unexpected results from dumpProperties: \n %s" % properties)
properties = test_widget.getProperties()
self.assertEqual(
properties["label_size"], 6,
"Unexpected results from getProperties: %s" % properties)
test_widget.setProperties({"start_x_position": 12})
self.assertEqual(
test_widget.start_x_position, 12,
"setProperties doesn't seem to work right: %s" %
test_widget.start_x_position)
def test_widget(self):
"""Try widget derived functionality.
"""
test_widget = BasicChromosome.ChromosomeSegment()
expected_string = "chr_percent = 0.25"
# trick to write the properties to a string
save_stdout = sys.stdout
new_stdout = cStringIO.StringIO()
sys.stdout = new_stdout
test_widget.dumpProperties()
properties = new_stdout.getvalue()
sys.stdout = save_stdout
assert properties.find(expected_string) >= 0, \
"Unexpected results from dumpProperties: \n %s" % properties
properties = test_widget.getProperties()
assert properties.has_key("label_size") \
and properties["label_size"] == 6, \
"Unexpected results from getProperties: %s" % properties
test_widget.setProperties({"start_x_position": 12})
assert test_widget.start_x_position == 12, \
"setProperties doesn't seem to work right: %s" \
% test_widget.start_x_position
def test_fill_chromosome(self):
"""Test filling out the information on a chromosome."""
test_chr = BasicChromosome.Chromosome("1")
self.count_display.add_count(self.names[2], 5)
self.count_display.add_count(self.names[1], 2)
self.count_display.add_label(self.names[3], "Test-Label")
new_chr = self.count_display.fill_chromosome(test_chr)
def draw_page(selected_refs):
chr_diagram = BasicChromosome.Organism()
chr_diagram.page_size = page_size
chr_diagram._legend_height = 0
for name, length in selected_refs:
features = []
# Add the N-regions
for n, start, end in n_regions:
if n == name:
# Want to use a border and fill color, needs Biopython 1.62
features.append((start, end, None, "", colors.black, colors.lightgrey))
for n, start, end, strand, caption, color, fill_color in all_features:
if n == name:
features.append((start, end, strand, caption, color, fill_color))
cur_chromosome = BasicChromosome.Chromosome(name)
cur_chromosome.scale_num = max_length + 2 * telomere_length
cur_chromosome.chr_percent = chr_percentage
cur_chromosome.label_sep_percent = label_percentage
cur_chromosome.label_size = label_size
cur_chromosome._color_labels = True
# Add an opening spacer (to center all chromosomes vertically)
space = BasicChromosome.SpacerSegment()
space.scale = (cur_chromosome.scale_num - length) * 0.5 - telomere_length
space.chr_percent = chr_percentage
cur_chromosome.add(space)
# Add an opening telomere
start = BasicChromosome.TelomereSegment()
start.scale = telomere_length
start.chr_percent = chr_percentage
cur_chromosome.add(start)
# Add a body - using bp as the scale length here.
body = BasicChromosome.AnnotatedChromosomeSegment(length, features, colors.blue)
body.scale = length
body.chr_percent = chr_percentage
cur_chromosome.add(body)
# Add a closing telomere
end = BasicChromosome.TelomereSegment(inverted=True)
end.scale = telomere_length
end.chr_percent = chr_percentage
cur_chromosome.add(end)
# Add an closing spacer
space = BasicChromosome.SpacerSegment()
space.scale = (cur_chromosome.scale_num - length) * 0.5 - telomere_length
space.chr_percent = chr_percentage
cur_chromosome.add(space)
# This chromosome is done
chr_diagram.add(cur_chromosome)
print("%s %i %i" % (name, length, len(features)))
return chr_diagram
def test_simple_organism(self):
"""Test the basic functionality of drawing an organism."""
pdf_organism = BasicChromosome.Organism()
# add chromosomes
for chr_name in ["I", "II", "III", "IV"]:
cur_chromosome = load_chromosome(chr_name)
pdf_organism.add(cur_chromosome)
pdf_organism.draw(self.test_file, "Test organism")
def _simple_organism(self, filename, format):
"""Output a simple organism to given format."""
test_organism = BasicChromosome.Organism(format)
test_file = os.path.join("Graphics", filename)
# add chromosomes
for chr_name in ["I", "II", "III", "IV"]:
cur_chromosome = load_chromosome(chr_name)
test_organism.add(cur_chromosome)
test_organism.draw(test_file, "Test organism")
def build_chrom_diagram(features, chr_sizes, sample_id, title=None):
"""Create a PDF of color-coded features on chromosomes."""
max_chr_len = max(chr_sizes.values())
chr_diagram = BC.Organism()
chr_diagram.page_size = PAGE_SIZE
chr_diagram.title_size = 18
for chrom, length in list(chr_sizes.items()):
chrom_features = features.get(chrom)
if not chrom_features:
continue
body = BC.AnnotatedChromosomeSegment(length, chrom_features)
body.label_size = 4
body.scale = length
body.chr_percent = CHROM_FATNESS
# Create opening and closing telomeres
tel_start = BC.TelomereSegment()
tel_start.scale = TELOMERE_LENGTH
tel_start.chr_percent = CHROM_FATNESS
tel_end = BC.TelomereSegment(inverted=True)
tel_end.scale = TELOMERE_LENGTH
tel_end.chr_percent = CHROM_FATNESS
# Assemble the chromosome diagram in order
cur_chromosome = BC.Chromosome(chrom)
cur_chromosome.title_size = 14
# Set the scale to the MAXIMUM length plus the two telomeres in bp,
# want the same scale used on all chromosomes so they can be
# compared to each other
cur_chromosome.scale_num = max_chr_len + 2 * TELOMERE_LENGTH
cur_chromosome.add(tel_start)
cur_chromosome.add(body)
cur_chromosome.add(tel_end)
chr_diagram.add(cur_chromosome)
if not title:
title = "Sample " + sample_id
return bc_organism_draw(chr_diagram, title)
def test_simple_organism_ps(self):
"""Output a simple organism to a postscript file.
"""
ps_organism = BasicChromosome.Organism('eps')
ps_file = os.path.join("Graphics", "organism.eps")
# add chromosomes
for chr_name in ["I", "II", "III", "IV"]:
cur_chromosome = load_chromosome(chr_name)
ps_organism.add(cur_chromosome)
ps_organism.draw(ps_file, "Test organism")
def bc_chromosome_draw_label(self, cur_drawing, label_name):
"""Monkeypatch to Bio.Graphics.BasicChromosome.Chromosome._draw_label.
Draw a label for the chromosome. Mod: above the chromosome, not below.
"""
# Center on chromosome image
x_position = 0.5 * (self.start_x_position + self.end_x_position)
# Place at the bottom of the diagram?
y_position = self.start_y_position + 0.1 * inch # was: self.end_y_position
label_string = BC.String(x_position, y_position, label_name)
label_string.fontName = 'Times-BoldItalic'
label_string.fontSize = self.title_size
label_string.textAnchor = 'middle'
cur_drawing.add(label_string)
def load_chrom(chr_name):
""" Generate a chromosome with information
"""
cur_chromosome = BasicChromosome.Chromosome(chr_name[0])
chr_segment_info = chr_name[1]
for seg_info_num in range(len(chr_segment_info)):
label, color, scale = chr_segment_info[seg_info_num]
# make the top and bottom telomeres
if seg_info_num == 0:
cur_segment = BasicChromosome.TelomereSegment()
elif seg_info_num == len(chr_segment_info) - 1:
cur_segment = BasicChromosome.TelomereSegment(1)
# otherwise, they are just regular segments
else:
cur_segment = BasicChromosome.ChromosomeSegment()
cur_segment.label = label
cur_segment.label_size = 12
cur_segment.fill_color = color
cur_segment.scale = scale
cur_chromosome.add(cur_segment)
cur_chromosome.scale_num = max(END) + (max(END) * .04)
return cur_chromosome
def test_random_organism(self):
"""Generate an organism with random chromosome info."""
random_file = os.path.join("Graphics", "random_organism.pdf")
pdf_organism = BasicChromosome.Organism()
all_segs = []
all_chrs = []
num_chrs = random.randrange(1, 15)
for chr_name in range(num_chrs):
cur_chromosome, num_segs = load_random_chromosome(str(chr_name))
all_chrs.append(cur_chromosome)
all_segs.append(num_segs)
# scale all of the chromosomes by the maximum number of segments
max_segs = max(all_segs)
for chr in all_chrs:
chr.scale_num = max_segs
pdf_organism.add(chr)
pdf_organism.draw(random_file, "Randomly generated Organism")
for f in handle:
if f.startswith(';'):
continue
tmplist = f.split()
tmp_feature = (float(tmplist[1]) * 1000, float(tmplist[1]) * 1000,
'0', tmplist[1] + ' : ' + tmplist[0], 'black')
features.append(tmp_feature)
return features
if __name__ == "__main__":
max_length = float(sys.argv[2]) * 1000
telomere_length = 10000
chr_diagram = BasicChromosome.Organism()
chr_diagram.page_size = (15 * cm, 30 * cm)
features = group2features(sys.argv[1])
group = BasicChromosome.Chromosome(sys.argv[3])
group.scale_num = max_length + 2 * telomere_length
start = BasicChromosome.TelomereSegment()
start.scale = telomere_length
group.add(start)
body = BasicChromosome.AnnotatedChromosomeSegment(max_length, features)
body.scale = max_length
group.add(body)
end = BasicChromosome.TelomereSegment(inverted=True)
## draw a chromosome for Brassica rapa
'''
from reportlab.lib.units import cm
from Bio import SeqIO
from Bio.Graphics import BasicChromosome
entries = [("A01", 26791027), ("A02", 26939825), ("A03", 31765687),
("A04", 19269588), ("A05", 25303531), ("A06", 25210367),
("A07", 25876095), ("A08", 20826944), ("A09", 38884799),
("A10", 16405179)]
max_len = 38884799 #Could compute this
telomere_length = 1000000
chr_diagram = BasicChromosome.Organism()
chr_diagram.page_size = (29.7 * cm, 21 * cm) #A4 landscape
for name, length in entries:
cur_chromosome = BasicChromosome.Chromosome(name)
#Set the scale to the MAXIMUM length plus the two telomeres in bp,
#want the same scale used on all five chromosomes so they can be
#compared to each other
cur_chromosome.scale_num = max_len + 2 * telomere_length
#Add an opening telomere
start = BasicChromosome.TelomereSegment()
start.scale = telomere_length
cur_chromosome.add(start)
#Add a body - using bp as the scale length here.
def check_simple_tRNA(self, filename, use_seqfeatures=False):
f1 = [
(111889, 111961, -1, 'G01270'), (306383, 306456, 1, 'G01870'),
(309274, 309347, -1, 'G01890'), (515493, 515566, 1, 'G02480'),
(552639, 552711, 1, 'G02600'), (604401, 604474, 1, 'G02760'),
(877648, 877720, 1, 'G03515'), (892513, 892585, 1, 'G03570'),
(909809, 909882, -1, 'G03640'), (1159021, 1159092, 1, 'G04320'),
(1324921, 1324959, 1, 'G04720'), (1583770, 1583844, -1, 'G05390'),
(1817398, 1817470, 1, 'G05980'), (1978082, 1978156, 1, 'G06480'),
(2025354, 2025427, 1, 'G06610'), (2107396, 2107467, -1, 'G06860'),
(2111146, 2111217, -1, 'G06880'), (2177883, 2177957, 1, 'G07100'),
(2334818, 2334891, 1, 'G07580'), (2406830, 2406902, -1, 'G07760'),
(2588521, 2588593, 1, 'G08240'), (2846538, 2846611, -1, 'G08870'),
(2879305, 2879377, 1, 'G08950'), (2939418, 2939490, 1, 'G09110'),
(3431185, 3431257, -1, 'G10440'), (3676606, 3676644, 1, 'G11010'),
(3678774, 3678848, -1, 'G11030'), (3881528, 3881608, 1, 'G11550'),
(3914628, 3914700, -1, 'G11640'), (4266985, 4267059, -1, 'G12510'),
(4285884, 4285956, -1, 'G12590'), (4440211, 4440284, 1, 'G13010'),
(4522705, 4522779, -1, 'G13240'), (4709631, 4709703, 1, 'G13720'),
(4741995, 4742068, 1, 'G13840'), (4743091, 4743164, 1, 'G13850'),
(5189681, 5189755, -1, 'G15090'), (5309641, 5309713, -1, 'G15450'),
(5380901, 5380983, 1, 'G15650'), (5518055, 5518128, -1, 'G16100'),
(5619464, 5619537, -1, 'G16450'), (6038749, 6038831, 1, 'G17570'),
(6075812, 6075884, 1, 'G17660'), (6075937, 6076011, -1, 'G17670'),
(6345756, 6345828, 1, 'G18430'), (6488645, 6488726, 1, 'G18820'),
(6948850, 6948934, -1, 'G20040'), (6995272, 6995344, -1, 'G20170'),
(7004504, 7004576, 1, 'G20210'), (7016506, 7016579, 1, 'G20250'),
(7082657, 7082729, 1, 'G20420'), (7242749, 7242821, -1, 'G20820'),
(7499721, 7499793, -1, 'G21420'), (7656108, 7656180, -1, 'G21800'),
(7884405, 7884443, -1, 'G22320'), (8520278, 8520352, -1, 'G24080'),
(9143796, 9143870, 1, 'G26430'), (9158169, 9158242, 1, 'G26490'),
(10089422, 10089494, 1, 'G28720'), (10089883, 10089955, 1,
'G28730'),
(10090353, 10090425, 1, 'G28740'), (10090754, 10090826, 1,
'G28750'),
(10092310, 10092382, 1, 'G28770'), (10092786, 10092858, 1,
'G28780'),
(10093294, 10093366, 1, 'G28790'), (10093731, 10093803, 1,
'G28800'),
(10094158, 10094230, 1, 'G28810'), (10096936, 10097008, 1,
'G28820'),
(10097099, 10097171, 1, 'G28830'), (10097703, 10097775, 1,
'G28840'),
(10098638, 10098710, 1, 'G28850'), (10099064, 10099136, 1,
'G28860'),
(10099410, 10099482, 1, 'G28870'), (10099812, 10099884, 1,
'G28880'),
(10100258, 10100330, 1, 'G28890'), (10101013, 10101085, 1,
'G28900'),
(10101585, 10101657, 1, 'G28910'), (10101978, 10102050, 1,
'G28920'),
(10106075, 10106147, 1, 'G28930'), (10106513, 10106585, 1,
'G28940'),
(10106883, 10106955, 1, 'G28950'), (10107634, 10107706, 1,
'G28970'),
(10108374, 10108446, 1, 'G28980'),
(10108695, 10108767, 1, 'G28990'),
(10207291, 10207364, -1, 'G29210'),
(10756703, 10756776, 1, 'G30430'),
(10963553, 10963627, -1, 'G30830'),
(11104093, 11104167, 1, 'G31110'),
(11797227, 11797265, -1, 'G32620'),
(12097258, 12097327, -1, 'G33370'),
(13687637, 13687710, 1, 'G36350'),
(15733055, 15733127, -1, 'G42120'),
(16588144, 16588216, -1, 'G43820'),
(17159046, 17159118, 1, 'G45234'), (17159799, 17159871, 1,
'G45236'),
(17160970, 17161042, 1, 'G45238'), (17161418, 17161490, 1,
'G45240'),
(17162967, 17163039, 1, 'G45242'), (17163408, 17163480, 1,
'G45244'),
(17164461, 17164533, 1, 'G45246'),
(17735509, 17735582, 1, 'G48080'),
(18139265, 18139337, -1, 'G49020'),
(18234146, 18234220, -1, 'G49280'),
(18312570, 18312607, 1, 'G49460'), (18391469, 18391542, 1,
'G49690'),
(18556666, 18556746, 1, 'G50070'), (18561567, 18561647, 1,
'G50100'),
(19428223, 19428297, 1, 'G52170'),
(19502087, 19502161, -1, 'G52350'),
(19688850, 19688887, -1, 'G52860'),
(19851640, 19851714, 1, 'G53220'),
(19929506, 19929578, -1, 'G53410'),
(20416594, 20416667, -1, 'G54670'),
(20794976, 20795058, 1, 'G55625'), (21272451, 21272533, 1,
'G56730'),
(21272786, 21272823, 1, 'G56740'), (21273216, 21273253, 1,
'G56750'),
(21273960, 21274042, 1, 'G56760'), (21274295, 21274332, 1,
'G56770'),
(21274725, 21274762, 1, 'G56780'), (21275469, 21275551, 1,
'G56790'),
(21275804, 21275841, 1, 'G56800'), (21276234, 21276271, 1,
'G56810'),
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(7387890, 7387962, 1, 'G22315'), (7981400, 7981472, 1, 'G23665'),
(8906418, 8906502, 1, 'G25585'), (8946826, 8946899, -1, 'G25625'),
(9815405, 9815477, -1, 'G27715'),
(11802284, 11802356, 1, 'G32017'),
(13823211, 13823284, -1, 'G35605'),
(15049737, 15049811, -1, 'G37795'),
(15242547, 15242621, 1, 'G38155'),
(15593086, 15593160, 1, 'G38905'),
(15844253, 15844325, -1, 'G39535'),
(15993514, 15993587, 1, 'G39895'),
(16256865, 16256937, -1, 'G40545'),
(16427812, 16427893, 1, 'G40945'),
(16524760, 16524832, -1, 'G41265'),
(16655393, 16655477, 1, 'G41605'),
(16684663, 16684735, -1, 'G41675'),
(17476402, 17476475, -1, 'G43455'),
(17512768, 17512839, -1, 'G43535'),
(17856811, 17856883, -1, 'G44283'),
(17894906, 17894979, -1, 'G44375'),
(18058014, 18058088, 1, 'G44705'),
(18560206, 18560278, -1, 'G45715'),
(18576071, 18576143, 1, 'G45745'),
(18715888, 18715960, -1, 'G46105'),
(18807534, 18807614, 1, 'G46325'), (18924749, 18924821, 1,
'G46595'),
(19658828, 19658900, 1, 'G48465'),
(19761400, 19761472, -1, 'G48675'),
(19820360, 19820398, 1, 'G48835'), (20064048, 20064120, 1,
'G49435'),
(20692447, 20692519, 1, 'G50805'),
(20758903, 20758940, -1, 'G50995'),
(20773555, 20773637, 1, 'G51055'),
(21275059, 21275141, -1, 'G52355'),
(21318105, 21318189, -1, 'G52495'),
(21418369, 21418441, 1, 'G52815'),
(21740339, 21740410, -1, 'G53487'),
(22091631, 22091704, 1, 'G54365'),
(22094087, 22094160, 1, 'G54375'),
(22304851, 22304923, -1, 'G54865'),
(22355897, 22355970, -1, 'G55045'),
(22357726, 22357799, -1, 'G55055'),
(22501995, 22502068, -1, 'G55505'),
(22845356, 22845430, 1, 'G56365'), (22973066, 22973138, 1,
'G56745'),
(23071996, 23072070, -1, 'G56975'),
(23463219, 23463291, 1, 'G57885'), (23661936, 23662018, 1,
'G58495'),
(23861431, 23861503, 1, 'G59055'), (23971167, 23971239, 1,
'G59385'),
(23974655, 23974727, 1, 'G59395'),
(24157171, 24157245, -1, 'G59945'),
(24279805, 24279886, 1, 'G60285'), (24547401, 24547474, 1,
'G60963'),
(24548892, 24548964, 1, 'G60966'), (24684507, 24684579, 1,
'G61345'),
(24726891, 24726964, 1, 'G61445'), (24856205, 24856242, 1,
'G61835'),
(25347261, 25347333, 1, 'G63145'), (25801340, 25801414, 1,
'G64505'),
(25892619, 25892691, -1, 'G64735'),
(25942291, 25942372, 1, 'G64855'), (25989903, 25989976, 1,
'G65015'),
(26114755, 26114793, -1, 'G65305'),
(26174414, 26174496, -1, 'G65445'),
(26212684, 26212757, 1, 'G65535'),
(26238859, 26238933, -1, 'G65615'),
(26573248, 26573322, -1, 'G66535'),
(26585622, 26585696, 1, 'G66568'),
(26670495, 26670567, -1, 'G66755'),
(26699933, 26700004, -1, 'G66817'),
(26938897, 26938969, 1, 'G67455')
]
entries = [("Chr I", "NC_003070", 30432563, f1, colors.red),
("Chr II", "NC_003071", 19705359, f2, colors.green),
("Chr III", "NC_003074", 23470805, f3, colors.blue),
("Chr IV", "NC_003075", 18585042, f4, colors.orange),
("Chr V", "NC_003076", 26992728, f5, colors.purple)]
max_length = max([row[2] for row in entries])
chr_diagram = BasicChromosome.Organism()
for name, acc, length, features, color in entries:
if False:
#How I generated the values above... and tested passing in SeqFeatures
filename = "/Users/pjcock/Documents/comp_genomics/seed/%s.gbk" % acc
import os
if not os.path.isfile(filename):
continue
from Bio import SeqIO
record = SeqIO.read(filename, "gb")
assert length == len(record)
features = [f for f in record.features if f.type == "tRNA"]
print(name)
#Strip of the first three chars, AT# where # is the chr
print([(int(f.location.start), int(f.location.end), f.strand,
f.qualifiers['locus_tag'][0][3:]) for f in features])
#Output was copy and pasted to the script, see above.
#Continue test using SeqFeature objects!
#To test colours from the qualifiers,
for i, f in enumerate(features):
f.qualifiers['color'] = [str(i % 16)]
elif use_seqfeatures:
#Features as SeqFeatures
features = [
SeqFeature(FeatureLocation(start, end, strand),
qualifiers={
"name": [label],
"color": [color]
}) for (start, end, strand, label) in features
]
else:
#Features as 5-tuples
features = [(start, end, strand, label, color)
for (start, end, strand, label) in features]
#I haven't found a nice source of data for real Arabidopsis
#cytobands, so these three are made up at random!
cytobands = []
for color in [colors.gray, colors.darkgray, colors.slategray]:
start = (length - 1000000) * random.random()
end = min(length, start + 1000000)
#Draw these with black borders, and a grey fill
cytobands.append((start, end, 0, None, colors.black, color))
#Draw these with black borders, and a brown fill:
cytobands.append(
(0, 1000000, 0, "First 1 Mbp", colors.black, colors.brown))
cytobands.append((length - 1000000, length, 0, "Last 1 Mbp",
colors.black, colors.brown))
#Additional dummy entry to check fill colour on both strands,
if name == "Chr III":
cytobands.append(
(11000000, 13000000, -1, "Reverse", "red", "yellow"))
elif name == "Chr V":
cytobands.append((9500000, 11000000, +1, "Forward", colors.red,
colors.yellow))
#Create the drawing object for the chromosome
cur_chromosome = BasicChromosome.Chromosome(name)
#Set the length, adding an extra 20 percent for the tolomeres etc:
cur_chromosome.scale_num = max_length * 1.2
cur_chromosome.label_sep_percent = 0.15
#Add a dummy segment for allocating vertical space
#which can be used for feature label placement
spacer = BasicChromosome.SpacerSegment()
spacer.scale = 0.03 * max_length
cur_chromosome.add(spacer)
#Add an opening telomere
start = BasicChromosome.TelomereSegment()
start.scale = 0.02 * max_length
start.fill_color = colors.lightgrey
cur_chromosome.add(start)
#Add a body - using bp as the scale length here.
#Note we put the cytobands a start of combined list,
#as want them drawn underneath the tRNA markers.
body = BasicChromosome.AnnotatedChromosomeSegment(
length, cytobands + features)
body.scale = length
cur_chromosome.add(body)
#Add a closing telomere
end = BasicChromosome.TelomereSegment(inverted=True)
end.scale = 0.02 * max_length
end.fill_color = colors.lightgrey
cur_chromosome.add(end)
#Another spacer
spacer = BasicChromosome.SpacerSegment()
spacer.scale = 0.03 * max_length
cur_chromosome.add(spacer)
#This chromosome is done
chr_diagram.add(cur_chromosome)
with warnings.catch_warnings():
# BiopythonWarning: Too many labels to avoid overlap
warnings.simplefilter("ignore", BiopythonWarning)
chr_diagram.draw(filename, "Arabidopsis thaliana tRNA")
def call1draw(cvsfile, write_func, *args):
"""Call regions, then plot it in chromosome figure.
A combination of drawchrom and call1
"""
argv = args[0]
if len(argv) < 6:
sys.stderr.write(
"Need 6 extra arguments for 'call1draw', options <loc column> <score column> <cutoff> <min length> <max gap> <pdf filename>\ne.g. command: <0> <1> <0.5> <10000> <2000> <a.pdf>, means to use the first column as genome coordinations to call enriched regions from the second column, the threshold to call enriched region is 0.5, the minimum length of region is 10k, and the maximum gap to link two nearby regions is 2k. Then the figure will be saved in a.pdf.\n"
)
sys.exit()
cor_column = cvsfile.fieldnames[int(argv[0])]
var_column = cvsfile.fieldnames[int(argv[1])]
cutoff = float(argv[2])
min_len = int(argv[3])
max_gap = int(argv[4])
wtrack = WigTrackI()
add_func = wtrack.add_loc
for l in cvsfile:
cor = l.setdefault(cor_column, None)
var = l.setdefault(var_column, None)
if cor and var and cor != "NA" and var != "NA":
(chrom, start, end) = cor.split(".")
add_func(chrom, int(start), float(var))
wtrack.span = int(end) - int(start)
bpeaks = wtrack.call_peaks(cutoff=cutoff,
min_length=min_len,
max_gap=max_gap)
fhd = open(argv[5].replace("pdf", "bed"), "w")
fhd.write(bpeaks.tobed())
from Bio.Graphics import BasicChromosome
from reportlab.lib.colors import gray, black, white
entries = [("chrI", 15072419), ("chrII", 15279316), ("chrIII", 13783681),
("chrIV", 17493784), ("chrV", 20919398), ("chrX", 17718852)]
max_length = max([x[1] for x in entries])
chr_diagram = BasicChromosome.Organism()
for name, length in entries:
cur_chromosome = BasicChromosome.Chromosome(name)
#Set the length, adding and extra 20 percent for the tolomeres:
cur_chromosome.scale_num = max_length * 1.1
# Add an opening telomere
start = BasicChromosome.TelomereSegment()
start.scale = 0.05 * max_length
start.fill_color = gray
cur_chromosome.add(start)
#Add a body - using bp as the scale length here.
try:
cpeaks = bpeaks.peaks[name]
except:
cpeaks = []
body_regions = []
last_pos = 0
for p in cpeaks:
body_regions.append((p[0] - last_pos, white)) # outside regions
body_regions.append((p[1] - p[0], black)) # enriched regions
last_pos = p[1]
assert p[1] < length
body_regions.append((length - last_pos, white)) # last part
for b, c in body_regions:
body = BasicChromosome.ChromosomeSegment()
body.fill_color = c
body.scale = b
cur_chromosome.add(body)
#Add a closing telomere
end = BasicChromosome.TelomereSegment(inverted=True)
end.scale = 0.05 * max_length
end.fill_color = gray
cur_chromosome.add(end)
#This chromosome is done
chr_diagram.add(cur_chromosome)
chr_diagram.draw(argv[5],
"%s regions in Caenorhabditis elegans" % (var_column))
def combcall2draw(cvsfile, write_func, *args):
"""User specifies several columns to consider, this tool will call
regions where either of the column is above its threshold.
"""
argv = args[0]
if len(argv) < 6:
sys.stderr.write(
"Need 6 extra arguments for 'combcall2draw', options <loc column> <score column1[,score column2,...]> <cutoff1[,cutoff2,cutoff3]> <min length> <max gap> <pdf filename>\ne.g. command: <0> <1,2,3> <0.5,0.6,0.7> <10000> <2000> <a.pdf>, means to use the first column as genome coordinations to call enriched regions from the combinition of #1, #2 and #3, the thresholds to call enriched region are 0.5 for column 1, 0.6 for column 2 and 0.7 for column 3, the minimum length of region is 10k, and the maximum gap to link two nearby regions is 2k. Then the figure will be saved in a.pdf.\n"
)
sys.exit()
cor_column = cvsfile.fieldnames[int(argv[0])]
var_columns = map(lambda x: cvsfile.fieldnames[int(x)], argv[1].split(","))
cutoffs = map(float, argv[2].split(","))
min_len = int(argv[3])
max_gap = int(argv[4])
wtrack = WigTrackI(
) # combined track containing 1 if either of track is above cutoff
add_func = wtrack.add_loc
for l in cvsfile:
cor = l.setdefault(cor_column, None)
if not cor or cor == "NA":
continue
for i in range(len(var_columns)):
var_column = var_columns[i]
cutoff = cutoffs[i]
var = l.setdefault(var_column, None)
if var and var != "NA" and float(var) > cutoff:
(chrom, start, end) = cor.split(".")
add_func(chrom, int(start), 1.1)
break
wtrack.span = int(end) - int(start)
bpeaks = wtrack.call_peaks(cutoff=1.0, min_length=min_len, max_gap=max_gap)
#f = argv[5]
fhd = open(argv[5].replace("pdf", "bed"), "w")
fhd.write(bpeaks.tobed())
from Bio.Graphics import BasicChromosome
from reportlab.lib.colors import gray, black, white
entries = [("chrI", 15072419), ("chrII", 15279316), ("chrIII", 13783681),
("chrIV", 17493784), ("chrV", 20919398), ("chrX", 17718852)]
max_length = max([x[1] for x in entries])
chr_diagram = BasicChromosome.Organism()
for name, length in entries:
cur_chromosome = BasicChromosome.Chromosome(name)
#Set the length, adding and extra 20 percent for the tolomeres:
cur_chromosome.scale_num = max_length * 1.1
# Add an opening telomere
start = BasicChromosome.TelomereSegment()
start.scale = 0.05 * max_length
start.fill_color = gray
cur_chromosome.add(start)
#Add a body - using bp as the scale length here.
try:
cpeaks = bpeaks.peaks[name]
except:
cpeaks = []
body_regions = []
last_pos = 0
for p in cpeaks:
body_regions.append((p[0] - last_pos, white)) # outside regions
body_regions.append((p[1] - p[0], black)) # enriched regions
last_pos = p[1]
assert p[1] < length
body_regions.append((length - last_pos, white)) # last part
for b, c in body_regions:
body = BasicChromosome.ChromosomeSegment()
body.fill_color = c
body.scale = b
cur_chromosome.add(body)
#Add a closing telomere
end = BasicChromosome.TelomereSegment(inverted=True)
end.scale = 0.05 * max_length
end.fill_color = gray
cur_chromosome.add(end)
#This chromosome is done
chr_diagram.add(cur_chromosome)
chr_diagram.draw(argv[5], "Highlight regions in Caenorhabditis elegans")
if feat["type"] not in ftype_to_col.keys():
ftype_to_col[feat["type"]] = cols[type_id]
logh.write(f"{feat['type']}: {cols[type_id]}\n")
type_id += 1
features[feat["chrom"]].append(
SeqFeature(
location=FeatureLocation(int(feat["start"]), int(feat["end"])),
type=feat["type"],
qualifiers={"color": [ftype_to_col[feat["type"]]]},
)
)
max_len = max(entries.values())
telomere_length = 10000 # For illustration
chr_diagram = BasicChromosome.Organism(output_format="svg")
chr_diagram.page_size = (29.7 * cm, 21 * cm) # A4 landscape
for name, length in entries.items():
# features = [f for f in record.features if f.type == "tRNA"]
chrom_feat = features[name]
chrom_num = re.sub(r"^.*_([0-9]+)$", r"\1", name)
cur_chromosome = BasicChromosome.Chromosome(chrom_num)
# Set the scale to the MAXIMUM length plus the two telomeres in bp,
# want the same scale used on all five chromosomes so they can be
# compared to each other
cur_chromosome.scale_num = max_len + 2 * telomere_length
# Add an opening telomere
start = BasicChromosome.TelomereSegment()
def annotated_chromosomes(fasta, output, spname, homosnps, heterosnps, scale, \
telomere_length, window, lenlimit, verbose, multi=10 ):
"""Generate chromosome plot"""
#load bed files
homocountsdict, expcounts1, homofns = load_counts_beds(
homosnps, window, 0, verbose)
hetecountsdict, expcounts2, hetefns = load_counts_beds(
heterosnps, window, 0, verbose)
expcount1 = expcounts1[0]
expcount2 = expcounts2[0]
#get chromosome names and lengths
chr2length = {r.id: len(r) for r in SeqIO.parse(fasta, 'fasta')}
#total genome length
max_len = max(chr2length.values())
if verbose:
sys.stderr.write("%s chromosomes. The largest chromosome is %s bp\n" %
(len(chr2length), max_len))
#init diagram
chr_diagram = BasicChromosome.Organism()
multisize = 5
chr_diagram.page_size = (multi * 29.7 * cm * multisize,
multi * 21 * cm * multisize) #A4 landscape
chr_diagram.output_format = output.split('.')[-1]
chr_diagram.title_size = 20 * multi
#add chromosomes
for i, (name, length) in enumerate(
sorted(chr2length.items(), key=lambda x: x[1], reverse=True)):
'''features = [f for f in record.features if f.type=="tRNA"]
#Record an Artemis style integer color in the feature's qualifiers,
#1 = Black, 2 = Red, 3 = Green, 4 = blue, 5 =cyan, 6 = purple
for f in features: f.qualifiers["color"] = [index+2]'''
if length < lenlimit * 1e3:
continue
print i, name, length
cur_chromosome = BasicChromosome.Chromosome(
name.split()[0].split('|')[0])
#Set the scale to the MAXIMUM length plus the two telomeres in bp,
#want the same scale used on all five chromosomes so they can be
#compared to each other
cur_chromosome.scale_num = max_len + 2 * telomere_length
cur_chromosome.title_size = 12 * multi
#Add an opening telomere
start = BasicChromosome.TelomereSegment()
start.scale = telomere_length
cur_chromosome.add(start)
#get counts
bed1 = bed2 = ([], []), ([], [])
if homocountsdict:
bed1 = homocountsdict[name][0]
if hetecountsdict:
bed2 = hetecountsdict[name][0]
features = get_features(bed1, expcount1, bed2, expcount2, window)
#add scale marker
if not i:
for i in xrange(0, length, int(scale / 2)):
features.append(
(i, i + 1, 0, "%.2f Mb" % (i / scale, ), 'black'))
#Add a body - again using bp as the scale length here.
body = BasicChromosome.AnnotatedChromosomeSegment(length, features)
body.scale = length
body.label_size = 6 * multi
cur_chromosome.add(body)
#Add a closing telomere
end = BasicChromosome.TelomereSegment(inverted=True)
end.scale = telomere_length
cur_chromosome.add(end)
#This chromosome is done
chr_diagram.add(cur_chromosome)
#draw
chr_diagram.draw(output, spname)
if callback((key, value)):
newDict[key] = value
return newDict
# initialise max length variable and empty dictionaries for storing information on input fasta, reference busco table and query busco table
max_len=0
karyotype_dict = dict()
karyotype_content_dict = dict()
BUSCO_ref_dict = dict()
BUSCO_query_dict = dict()
colour_dict = dict()
# initialise karyotype plot variables
telomere_length = 200000
chr_diagram = BasicChromosome.Organism()
chr_diagram.page_size = (120 * cm, 60 * cm) # A4 landscape
##initialise features and feature dict
out=[]
feat_dict = dict()
print("Parsing fasta",end="\t")
### parse query fasta file into names and lengths
### set max length
for record in SeqIO.parse(args.queryfasta,"fasta"):
if len(record.seq) > max_len:
max_len = len(record.seq)
if len(record.seq) > args.min:
karyotype_content_dict[record.id] = []
karyotype_dict[record.id] = len(record.seq)
def bc_organism_draw(org, title, wrap=12):
"""Modified copy of Bio.Graphics.BasicChromosome.Organism.draw.
Instead of stacking chromosomes horizontally (along the x-axis), stack rows
vertically, then proceed with the chromosomes within each row.
Parameters
----------
org :
The chromosome diagram object being modified.
title : str
The output title of the produced document.
wrap : int
Maximum number of chromosomes per row; the remainder will be wrapped to
the next row(s).
"""
margin_top = 1.25 * inch
margin_bottom = 0.1 * inch
margin_side = 0.5 * inch
width, height = org.page_size
cur_drawing = BC.Drawing(width, height)
# Draw the title text
title_string = BC.String(width / 2, height - margin_top + .5 * inch, title)
title_string.fontName = 'Helvetica-Bold'
title_string.fontSize = org.title_size
title_string.textAnchor = "middle"
cur_drawing.add(title_string)
# Layout subcomponents (individual chromosomes), wrapping into rows
if len(org._sub_components) > 0:
nrows = math.ceil(len(org._sub_components) / wrap)
x_pos_change = (width - 2 * margin_side) / wrap
y_pos_change = (height - margin_top - margin_bottom) / nrows
cur_x_pos = margin_side
cur_row = 0
for i, sub_component in enumerate(org._sub_components):
if i % wrap == 0 and i != 0:
cur_row += 1
cur_x_pos = margin_side
# Set the page coordinates of the chromosome drawing
sub_component.start_x_position = cur_x_pos + 0.05 * x_pos_change
sub_component.end_x_position = cur_x_pos + 0.95 * x_pos_change
sub_component.start_y_position = (height - margin_top -
y_pos_change * cur_row)
sub_component.end_y_position = (margin_bottom + y_pos_change *
(nrows - cur_row - 1))
# Render the chromosome drawing
sub_component.draw(cur_drawing)
# Update the locations for the next chromosome
cur_x_pos += x_pos_change
# Draw a legend
# (Rect coordinates are: left, bottom, width, height)
# Bounding box -- near-bottom, center
cur_drawing.add(
BC.Rect(width / 2 - .8 * inch,
.5 * inch,
1.6 * inch,
.4 * inch,
fillColor=colors.white))
# Red box & label -- in left half of bounding box
cur_drawing.add(
BC.Rect(width / 2 - .7 * inch,
.6 * inch,
.2 * inch,
.2 * inch,
fillColor=colors.Color(.8, .2, .2)))
cur_drawing.add(
BC.String(width / 2 - .42 * inch,
.65 * inch,
"Gain",
fontName='Helvetica',
fontSize=12))
# Blue box & label -- in right half of bounding box
cur_drawing.add(
BC.Rect(width / 2 + .07 * inch,
.6 * inch,
.2 * inch,
.2 * inch,
fillColor=colors.Color(.2, .2, .8)))
cur_drawing.add(
BC.String(width / 2 + .35 * inch,
.65 * inch,
"Loss",
fontName='Helvetica',
fontSize=12))
# Let the caller take care of writing to the file...
return cur_drawing
('AT2G28000', (2, 11933524, 11936523)),
('AT3G03020', (3, 680920, 682009)),
('AT4G26000', (4, 13197255, 13199845)),
('AT4G32551', (4, 15707516, 15713587))]
break
if rx_rid.match(rid):
gids.append(rid)
else:
print("Bad format, please enter it again")
if rid != 'NODBDEMO':
samplemarkers = dblookup(gids)
crms = [[] for r in range(len(END))]
for x in samplemarkers:
crms[int(x[1][0]) - 1].append((x[0], x[1][1], x[1][2]))
crms_o = sortmarkers(crms, END)
chromo = getchromo(crms_o, END)
all_chr_info = [('Chr I', chromo[0]), ('Chr II', chromo[1]),
('Chr III', chromo[2]), ('Chr IV', chromo[3]),
('Chr V', chromo[4])]
organism = BasicChromosome.Organism()
organism.page_size = (29.7 * cm, 21 * cm) #A4 landscape
for chr_info in all_chr_info:
newcrom = (chr_info[0], addends(chr_info[1]))
organism.add(load_chrom(newcrom))
organism.draw('at.pdf', 'Arabidopsis thaliana')
# print j,gene[j][0],gene[j][3],genome[i].id
# sl(0.5)
direc = None #int(gene[j][3] + '1')
genome[i].features.append(
SeqFeature(FeatureLocation(centromeres[j][1],
centromeres[j][2],
strand=direc),
type='gene',
id=j,
qualifiers={'locus_tag': [centromeres[j][4]]}))
## telomere length - rounded ends of chromosome size
max_len = max(lengths)
telomere_length = 40000
chr_diagram = BasicChromosome.Organism()
#chr_diagram.page_size = (60*cm, 21*cm)
chr_diagram.page_size = (40 * cm, 21 * cm)
fill = colours.CMYKColorSep(0.4, 0, 0, 0.3, density=0.4, spotName='PMS_7496')
for index, (name, length) in enumerate(entries):
if length > 80000:
features = []
for i in acclis1:
for f in genome[name].features:
if f.id == i:
f.qualifiers['color'] = [2]
features += [f]
for i in cent_list:
for f in genome[name].features:
__author__ = 'mjohnpayne'
from Bio import SeqIO
from reportlab.lib.units import cm
from Bio.Graphics import BasicChromosome
from Bio.SeqRecord import SeqRecord
from Bio.SeqFeature import SeqFeature, FeatureLocation
from Bio.Alphabet import IUPAC
import sys
max_len = 6000000
telomere_length = 40000
chr_diagram = BasicChromosome.Organism()
chr_diagram.page_size = (60*cm, 21*cm)
chr_diagram.
chr_diagram.draw('/Users/mjohnpayne/Documents/PhD/Chromosome_plots/legend_test.pdf','legend_test')
def get(self): #查找和查询
s=entity.hosInfo(self.db)
#cent_code='004'
offset = int(self.get_argument('o',default='1'))
rowcount = int(self.get_argument('r',default='10'))
offset=(offset-1)*rowcount
no=self.get_argument("no",default='')
file_id=self.get_argument("file_id",default='')
cur=self.db.getCursor()
if no=='1':
sql="select a.path from public.file a where a.id=%s "%(file_id)
cur.execute(sql)
row = cur.fetchone()
rowdata={}
rowdata['rows']=row
print(row)
filename="/home/ubuntu/pythonff/mdt/mdt/mdtproject/trunk/app/"+row[0]
imgfile=filename[:-2]+"svg"
imgfile1=filename[:-2]+"1.svg"
print(filename)
print(imgfile)
record = SeqIO.read(filename, "genbank")
gd_diagram = GenomeDiagram.Diagram(record.id)
gd_track_for_features = gd_diagram.new_track(1, name="Annotated Features")
gd_feature_set = gd_track_for_features.new_set()
for feature in record.features:
if feature.type != "gene":
#Exclude this feature
continue
if len(gd_feature_set) % 2 == 0:
color = colors.blue
else:
color = colors.lightblue
gd_feature_set.add_feature(feature, sigil="ARROW",
color=color, label=True,
label_size = 14, label_angle=0)
#I want to include some strandless features, so for an example
#will use EcoRI recognition sites etc.
for site, name, color in [("GAATTC","EcoRI",colors.green),
("CCCGGG","SmaI",colors.orange),
("AAGCTT","HindIII",colors.red),
("GGATCC","BamHI",colors.purple)]:
index = 0
while True:
index = record.seq.find(site, start=index)
if index == -1 : break
feature = SeqFeature(FeatureLocation(index, index+len(site)))
gd_feature_set.add_feature(feature, color=color, name=name,
label=True, label_size = 10,
label_color=color)
index += len(site)
gd_diagram.draw(format="linear", pagesize='A4', fragments=4,
start=0, end=len(record))
#gd_diagram.write("plasmid_linear_nice.pdf", "PDF")
#gd_diagram.write("plasmid_linear_nice.eps", "EPS")
gd_diagram.write(imgfile, "SVG")
gd_diagram.draw(format="circular", circular=True, pagesize=(20*cm,20*cm),
start=0, end=len(record), circle_core = 0.5)
#gd_diagram.write("plasmid_circular_nice.pdf", "PDF")
#gd_diagram.write("plasmid_circular_nice.eps", "EPS")
gd_diagram.write(imgfile1, "SVG")
elif no=='2':
q=0
pdffile="/home/ubuntu/pythonff/mdt/mdt/mdtproject/trunk/app/uploads/tm/"+file_id+".pdf"
pdf="uploads/tm/"+file_id+".pdf"
file_id=file_id.split(',')
sql1="where a.id=%s "%(file_id[q])
for i in range(len(file_id)-1):
sql1=sql1+"or a.id=%s "%(file_id[q+1])
q=q+1
sql="select a.path,a.file_name from public.file a %s "%(sql1)
cur.execute(sql)
row = cur.fetchall()
print(row)
rowdata={}
rowdata['rows']=pdf
q=0
a=[]
entriess = []
entries = []
for i in range(len(row)):
filepath="/home/ubuntu/pythonff/mdt/mdt/mdtproject/trunk/app/"+row[q][0]
filename=row[q][1]
entriess.append((filename,filepath))
q=q+1
for(name,path) in entriess:
record=SeqIO.read(path,"fasta")
a.append(len(record))
entries.append((name,len(record)))
max_len = max(a)
telomere_length = 1000000 #For illustration
chr_diagram = BasicChromosome.Organism()
chr_diagram.page_size = (29.7*cm, 21*cm) #A4 landscape
for name, length in entries:
cur_chromosome = BasicChromosome.Chromosome(name)
#Set the scale to the MAXIMUM length plus the two telomeres in bp,
#want the same scale used on all five chromosomes so they can be
#compared to each other
cur_chromosome.scale_num = max_len + 2 * telomere_length
#Add an opening telomere
start = BasicChromosome.TelomereSegment()
start.scale = telomere_length
cur_chromosome.add(start)
#Add a body - using bp as the scale length here.
body = BasicChromosome.ChromosomeSegment()
body.scale = length
cur_chromosome.add(body)
#Add a closing telomere
end = BasicChromosome.TelomereSegment(inverted=True)
end.scale = telomere_length
cur_chromosome.add(end)
#This chromosome is done
chr_diagram.add(cur_chromosome)
chr_diagram.draw(pdffile, "Arabidopsis thaliana")
elif no=='3':
q=0
pdffile="/home/ubuntu/pythonff/mdt/mdt/mdtproject/trunk/app/uploads/tm/"+file_id+".pdf"
pdf="uploads/tm/"+file_id+".pdf"
file_id=file_id.split(',')
sql1="where a.id=%s "%(file_id[q])
for i in range(len(file_id)-1):
sql1=sql1+"or a.id=%s "%(file_id[q+1])
q=q+1
sql="select a.path,a.file_name from public.file a %s "%(sql1)
cur.execute(sql)
row = cur.fetchall()
print(row)
rowdata={}
rowdata['rows']=pdf
q=0
a=[]
entries = []
for i in range(len(row)):
filepath="/home/ubuntu/pythonff/mdt/mdt/mdtproject/trunk/app/"+row[q][0]
filename=row[q][1]
entries.append((filename,filepath))
q=q+1
for(name,path) in entries:
record=SeqIO.read(path,"genbank")
a.append(len(record))
max_len=max(a)
telomere_length = 1000000 #For illustration
chr_diagram = BasicChromosome.Organism()
chr_diagram.page_size = (29.7*cm, 21*cm) #A4 landscape
for index, (name, filename) in enumerate(entries):
record = SeqIO.read(filename,"genbank")
length = len(record)
features = [f for f in record.features if f.type=="tRNA"]
#Record an Artemis style integer color in the feature's qualifiers,
#1 = Black, 2 = Red, 3 = Green, 4 = blue, 5 =cyan, 6 = purple
for f in features: f.qualifiers["color"] = [index+2]
cur_chromosome = BasicChromosome.Chromosome(name)
#Set the scale to the MAXIMUM length plus the two telomeres in bp,
#want the same scale used on all five chromosomes so they can be
#compared to each other
cur_chromosome.scale_num = max_len + 2 * telomere_length
#Add an opening telomere
start = BasicChromosome.TelomereSegment()
start.scale = telomere_length
cur_chromosome.add(start)
#Add a body - again using bp as the scale length here.
body = BasicChromosome.AnnotatedChromosomeSegment(length, features)
body.scale = length
cur_chromosome.add(body)
#Add a closing telomere
end = BasicChromosome.TelomereSegment(inverted=True)
end.scale = telomere_length
cur_chromosome.add(end)
#This chromosome is done
chr_diagram.add(cur_chromosome)
chr_diagram.draw(pdffile, "Arabidopsis thaliana")
self.response(rowdata)
