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 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 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 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 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 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 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 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'),
(21276978, 21277060, 1, 'G56820'), (21277313, 21277350, 1,
'G56830'),
(21277743, 21277780, 1, 'G56840'), (21278487, 21278569, 1,
'G56850'),
(21278822, 21278859, 1, 'G56860'), (21279273, 21279310, 1,
'G56870'),
(21280016, 21280098, 1, 'G56880'), (21280351, 21280388, 1,
'G56890'),
(21280781, 21280818, 1, 'G56900'), (21281525, 21281607, 1,
'G56910'),
(21281860, 21281897, 1, 'G56920'), (21282311, 21282348, 1,
'G56930'),
(21283054, 21283136, 1, 'G56940'), (21283384, 21283421, 1,
'G56950'),
(21283842, 21283879, 1, 'G56960'), (21284586, 21284668, 1,
'G56970'),
(21284916, 21284953, 1, 'G56980'), (21285374, 21285411, 1,
'G56990'),
(21286118, 21286200, 1, 'G57000'), (21286448, 21286485, 1,
'G57010'),
(21286906, 21286943, 1, 'G57020'), (21287650, 21287732, 1,
'G57030'),
(21287980, 21288017, 1, 'G57040'), (21288438, 21288475, 1,
'G57050'),
(21289183, 21289265, 1, 'G57060'), (21289513, 21289550, 1,
'G57070'),
(21289970, 21290007, 1, 'G57080'), (21290714, 21290796, 1,
'G57090'),
(21291044, 21291081, 1, 'G57100'), (21291501, 21291538, 1,
'G57110'),
(21292245, 21292327, 1, 'G57120'), (21292574, 21292611, 1,
'G57130'),
(21293032, 21293069, 1, 'G57140'), (21293776, 21293858, 1,
'G57150'),
(21294109, 21294146, 1, 'G57160'), (21294567, 21294604, 1,
'G57170'),
(21295125, 21295207, 1, 'G57180'), (21295455, 21295492, 1,
'G57190'),
(21295912, 21295949, 1, 'G57200'), (21296656, 21296738, 1,
'G57210'),
(21296989, 21297026, 1, 'G57220'), (21297447, 21297484, 1,
'G57230'),
(21298005, 21298087, 1, 'G57240'), (21298335, 21298372, 1,
'G57250'),
(21298792, 21298829, 1, 'G57260'), (21299536, 21299618, 1,
'G57270'),
(21299869, 21299906, 1, 'G57280'), (21300327, 21300364, 1,
'G57290'),
(21300885, 21300967, 1, 'G57300'), (21301215, 21301252, 1,
'G57310'),
(21301673, 21301710, 1, 'G57320'), (21302417, 21302499, 1,
'G57330'),
(21302750, 21302787, 1, 'G57340'), (21303208, 21303245, 1,
'G57350'),
(21303766, 21303848, 1, 'G57360'), (21304096, 21304133, 1,
'G57370'),
(21304554, 21304591, 1, 'G57380'), (21305298, 21305380, 1,
'G57390'),
(21305631, 21305668, 1, 'G57400'), (21306089, 21306126, 1,
'G57410'),
(21306647, 21306729, 1, 'G57420'), (21306981, 21307018, 1,
'G57430'),
(21307441, 21307478, 1, 'G57440'), (21308184, 21308268, 1,
'G57450'),
(21308520, 21308557, 1, 'G57460'), (21308975, 21309012, 1,
'G57470'),
(21309719, 21309801, 1, 'G57480'), (21310053, 21310090, 1,
'G57490'),
(21310513, 21310550, 1, 'G57500'), (21311256, 21311340, 1,
'G57510'),
(21311592, 21311629, 1, 'G57520'),
(21312051, 21312088, 1, 'G57530'),
(21377983, 21378054, -1, 'G57710'),
(21887507, 21887589, -1, 'G59570'),
(22044276, 22044348, -1, 'G59880'),
(22317078, 22317149, -1, 'G60580'),
(22398301, 22398372, -1, 'G60820'),
(22401256, 22401327, -1, 'G60840'),
(22431831, 22431902, 1, 'G60910'),
(22481437, 22481511, -1, 'G61020'),
(22870422, 22870494, -1, 'G61880'),
(22890754, 22890834, 1, 'G61910'),
(23562849, 23562921, -1, 'G63510'),
(23671147, 23671219, -1, 'G63790'),
(23806215, 23806299, 1, 'G64120'), (23936799, 23936872, 1,
'G64420'),
(24490654, 24490736, -1, 'G65830'),
(25833316, 25833388, 1, 'G68770'), (25890198, 25890272, 1,
'G68860'),
(25931858, 25931931, 1, 'G68950'),
(25935739, 25935812, -1, 'G68970'),
(25944826, 25944898, 1, 'G69000'), (25993392, 25993466, 1,
'G69130'),
(26053140, 26053214, 1, 'G69300'),
(26385816, 26385888, -1, 'G70050'),
(26977050, 26977121, 1, 'G71700'), (27397046, 27397128, 1,
'G72780'),
(27792643, 27792715, 1, 'G73900'),
(28024043, 28024124, -1, 'G74570'),
(28031620, 28031701, 1, 'G74610'), (28188192, 28188264, 1,
'G75070'),
(28377149, 28377222, -1, 'G75570'),
(28411644, 28411717, 1, 'G75650'), (28444549, 28444621, 1,
'G75740'),
(28523645, 28523717, -1, 'G75970'),
(28531427, 28531499, 1, 'G76000'), (28639585, 28639667, 1,
'G76330'),
(28952447, 28952519, -1, 'G77040'),
(29007098, 29007180, -1, 'G77190'),
(29147983, 29148055, -1, 'G77560'),
(29448865, 29448903, -1, 'G78250'),
(29809015, 29809088, 1, 'G79240'), (29838009, 29838081, 1,
'G79290'),
(29838610, 29838682, 1, 'G79300'),
(30088888, 30088962, -1, 'G79980'),
(30178905, 30178977, -1, 'G80250'),
(30242675, 30242757, 1, 'G80430')
]
f2 = [
(102063, 102137, 1, 'G01160'), (706794, 706867, 1, 'G02600'),
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(1154381, 1154454, 1, 'G03790'), (3239653, 3239725, -1, 'G07742'),
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(3276436, 3276508, 1, 'G07746'), (3280859, 3280933, 1, 'G07748'),
(3290962, 3291034, 1, 'G07778'), (3303240, 3303312, -1, 'G07752'),
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(3369350, 3369437, 1, 'G07793'), (3383400, 3383474, -1, 'G07794'),
(3444359, 3444431, -1, 'G07756'), (3452973, 3453060, 1, 'G07757'),
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(3494772, 3494847, 1, 'G07761'), (3495008, 3495083, 1, 'G07762'),
(3495438, 3495509, 1, 'G07763'), (3496436, 3496508, 1, 'G07764'),
(3497354, 3497437, 1, 'G07765'), (3503518, 3503605, 1, 'G07766'),
(6953924, 6953961, -1, 'G15950'), (7046175, 7046247, 1, 'G16240'),
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(9291113, 9291185, 1, 'G21760'), (9400749, 9400823, 1, 'G22110'),
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(11781928, 11782000, -1, 'G27560'),
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(12645232, 12645305, -1, 'G29520'),
(12888667, 12888738, 1, 'G30180'), (12889810, 12889881, 1,
'G30190'),
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'G33660'),
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'G33900'),
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'G33920'),
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'G33940'),
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'G35220'),
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'G45390'),
(18963713, 18963786, 1, 'G46120'), (19351496, 19351569, 1,
'G47100'),
(19566924, 19566995, -1, 'G47740')
]
f3 = [
(259640, 259712, 1, 'G01705'), (469666, 469740, 1, 'G02315'),
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'G52765'),
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'G53775'),
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'G58165'),
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'G61755'),
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'G62245'),
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]
f4 = [
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'G28915'),
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'G31075'),
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'G32475'),
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'G34975'),
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'G36245'),
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'G39615'),
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]
f5 = [
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'G58495'),
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'G59385'),
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'G60963'),
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'G61345'),
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'G61835'),
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'G64505'),
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'G65015'),
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(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")
f.qualifiers['color'] = [8]
features += [f]
for i in acclis4:
for f in genome[name].features:
if f.id == i:
f.qualifiers['color'] = [10]
features += [f]
#for f in features: f.qualifiers["color"] = [index+2]
cur_chromosome = BasicChromosome.Chromosome(name)
cur_chromosome.scale_num = max_len + 2 * telomere_length
cur_chromosome.label_size = 8
cur_chromosome.chr_percent = 0.2
cur_chromosome.label_sep_percent = 0.1
#Add an opening telomere
start = BasicChromosome.TelomereSegment()
start.fill_color = fill
start.scale = telomere_length
cur_chromosome.add(start)
#Add a body - using bp as the scale length here.
body = BasicChromosome.AnnotatedChromosomeSegment(length, features)
body.scale = length
body.fill_color = fill
cur_chromosome.add(body)
#Add a closing telomere
end = BasicChromosome.TelomereSegment(inverted=True)
end.fill_color = fill
end.scale = telomere_length
cur_chromosome.add(end)
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)
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)
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")
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 main():
from taolib.CoreLib.Parser.BedIO import parse_BED
from Bio.Graphics import BasicChromosome
if len(sys.argv) < 3:
sys.stderr.write(
"Draw Chromosome Figure\nneed 2 paras: %s <dbname> <color> <bed file>\n"
% sys.argv[0])
sys.exit(1)
try:
entries = get_chrom_length(sys.argv[1])
except:
error("Error!")
sys.exit(1)
col = getCol(sys.argv[2])
bpeaks = parse_BED(open(sys.argv[3]))
pdffile = sys.argv[3] + ".pdf"
max_length = max([x[1] for x in entries])
chr_diagram = BasicChromosome.Organism()
for name, length in entries:
cur_chromosome = BasicChromosome.Chromosome(name)
cur_chromosome.title_size = 0.5
#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], col)) # 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(pdffile, "Highlight regions")
