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 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 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'),
(846853, 846926, -1, 'G02900'), (1054714, 1054787, -1, 'G03490'),
(1113980, 1114052, -1, 'G03660'), (1123386, 1123458, -1, 'G03700'),
(1154381, 1154454, 1, 'G03790'), (3239653, 3239725, -1, 'G07742'),
(3255828, 3255902, -1, 'G07743'), (3268803, 3268883, 1, 'G07745'),
(3276436, 3276508, 1, 'G07746'), (3280859, 3280933, 1, 'G07748'),
(3290962, 3291034, 1, 'G07778'), (3303240, 3303312, -1, 'G07752'),
(3303350, 3303425, -1, 'G07753'), (3303781, 3303819, -1, 'G07754'),
(3328666, 3328739, -1, 'G07755'), (3332674, 3332756, 1, 'G07792'),
(3369350, 3369437, 1, 'G07793'), (3383400, 3383474, -1, 'G07794'),
(3444359, 3444431, -1, 'G07756'), (3452973, 3453060, 1, 'G07757'),
(3462074, 3462148, 1, 'G07758'), (3494378, 3494416, 1, 'G07759'),
(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'),
(7749793, 7749867, 1, 'G17810'), (7962758, 7962832, -1, 'G18310'),
(9144435, 9144507, 1, 'G21360'), (9241319, 9241356, -1, 'G21570'),
(9273888, 9273969, -1, 'G21670'), (9277742, 9277814, -1, 'G21700'),
(9291113, 9291185, 1, 'G21760'), (9400749, 9400823, 1, 'G22110'),
(9456888, 9456962, -1, 'G22220'), (9472660, 9472733, -1, 'G22280'),
(9509359, 9509433, 1, 'G22380'), (9598106, 9598179, 1, 'G22580'),
(9810296, 9810368, -1, 'G23020'),
(10066525, 10066597, -1, 'G23650'),
(10380655, 10380728, 1, 'G24380'),
(10820917, 10820990, 1, 'G25400'),
(11122756, 11122837, -1, 'G26090'),
(11781928, 11782000, -1, 'G27560'),
(11871230, 11871302, -1, 'G27850'),
(12336079, 12336151, 1, 'G28730'),
(12346827, 12346899, 1, 'G28770'),
(12478849, 12478921, -1, 'G29030'),
(12645232, 12645305, -1, 'G29520'),
(12888667, 12888738, 1, 'G30180'), (12889810, 12889881, 1,
'G30190'),
(12983024, 12983095, -1, 'G30450'),
(13144312, 13144385, -1, 'G30850'),
(13658350, 13658425, 1, 'G32110'),
(14054465, 14054503, -1, 'G33140'),
(14250206, 14250278, 1, 'G33650'), (14251774, 14251846, 1,
'G33660'),
(14357464, 14357536, 1, 'G33890'), (14358437, 14358509, 1,
'G33900'),
(14359269, 14359341, 1, 'G33910'), (14360221, 14360293, 1,
'G33920'),
(14360734, 14360806, 1, 'G33930'), (14361176, 14361248, 1,
'G33940'),
(14362215, 14362287, 1, 'G33950'), (14363133, 14363205, 1,
'G33960'),
(14363599, 14363671, 1, 'G33970'),
(14750553, 14750627, -1, 'G34950'),
(14757142, 14757213, 1, 'G34985'), (14847685, 14847723, 1,
'G35220'),
(15175940, 15176014, 1, 'G36140'), (15176656, 15176736, 1,
'G36150'),
(15215480, 15215517, -1, 'G36280'),
(15327312, 15327395, 1, 'G36510'),
(15327463, 15327546, -1, 'G36520'),
(15353238, 15353311, 1, 'G36600'),
(15477287, 15477324, -1, 'G36860'),
(15923894, 15923967, 1, 'G38030'),
(16525641, 16525713, -1, 'G39600'),
(16525846, 16525918, 1, 'G39610'),
(16646857, 16646929, -1, 'G39860'),
(17545780, 17545862, -1, 'G42020'),
(17667855, 17667926, 1, 'G42420'), (17880766, 17880839, 1,
'G42970'),
(18002649, 18002721, -1, 'G43300'),
(18317052, 18317134, -1, 'G44320'),
(18576985, 18577058, 1, 'G45020'), (18710751, 18710824, 1,
'G45390'),
(18963713, 18963786, 1, 'G46120'), (19351496, 19351569, 1,
'G47100'),
(19566924, 19566995, -1, 'G47740')
]
f3 = [
(259640, 259712, 1, 'G01705'), (469666, 469740, 1, 'G02315'),
(476808, 476880, 1, 'G02335'), (586092, 586174, 1, 'G02715'),
(981975, 982047, 1, 'G03845'), (984105, 984177, 1, 'G03852'),
(1220234, 1220307, 1, 'G04525'), (1601343, 1601415, -1, 'G05525'),
(1707743, 1707815, -1, 'G05755'), (1738796, 1738870, 1, 'G05835'),
(1843329, 1843400, -1, 'G06105'), (1920038, 1920110, -1, 'G06335'),
(2104961, 2105033, -1, 'G06665'), (2222251, 2222324, 1, 'G07025'),
(2232470, 2232506, -1, 'G07055'), (2253680, 2253762, -1, 'G07115'),
(2285607, 2285679, 1, 'G07185'), (2918418, 2918492, -1, 'G09505'),
(2944616, 2944698, 1, 'G09585'), (2945700, 2945782, -1, 'G09595'),
(3090548, 3090631, 1, 'G10015'), (3096220, 3096293, 1, 'G10035'),
(3238371, 3238407, -1, 'G10415'), (3535151, 3535224, 1, 'G11285'),
(3575849, 3575923, 1, 'G11395'), (3622697, 3622769, -1, 'G11505'),
(3942012, 3942084, 1, 'G12385'), (3995103, 3995176, -1, 'G12585'),
(4254534, 4254615, 1, 'G13223'), (4330778, 4330850, 1, 'G13335'),
(4998147, 4998219, 1, 'G14855'), (5068300, 5068374, -1, 'G15055'),
(5275155, 5275228, 1, 'G15585'), (5632857, 5632930, 1, 'G16552'),
(6483945, 6484019, -1, 'G18815'), (6540636, 6540673, 1, 'G18952'),
(6663713, 6663786, 1, 'G19235'), (7104314, 7104398, 1, 'G20365'),
(7224223, 7224296, -1, 'G20655'), (7319582, 7319664, -1, 'G20885'),
(7567399, 7567471, -1, 'G21475'), (9373610, 9373684, -1, 'G25715'),
(9840420, 9840494, 1, 'G26747'), (10211564, 10211636, 1, 'G27555'),
(10319498, 10319570, 1, 'G27825'), (10325875, 10325947, 1,
'G27845'),
(10753667, 10753740, 1, 'G28685'),
(10760629, 10760702, -1, 'G28695'),
(11076814, 11076886, 1, 'G29095'),
(11961645, 11961718, 1, 'G30345'),
(16438025, 16438097, -1, 'G44955'),
(16896875, 16896949, 1, 'G45935'), (16902623, 16902697, 1,
'G45955'),
(16905147, 16905221, 1, 'G45965'), (17160736, 17160808, 1,
'G46585'),
(17275564, 17275646, 1, 'G46875'),
(17905395, 17905467, 1, 'G48275'),
(17985575, 17985611, -1, 'G48515'),
(18080062, 18080134, 1, 'G48745'),
(18518796, 18518870, 1, 'G49925'),
(18755788, 18755860, -1, 'G50505'),
(18837020, 18837092, 1, 'G50665'), (18907851, 18907924, 1,
'G50835'),
(18928413, 18928487, 1, 'G50895'),
(19008621, 19008694, -1, 'G51135'),
(19044371, 19044443, -1, 'G51265'),
(19403651, 19403723, -1, 'G52285'),
(19420345, 19420417, -1, 'G52345'),
(19511965, 19512045, 1, 'G52565'), (19566013, 19566085, 1,
'G52765'),
(19648105, 19648188, 1, 'G52955'), (19935354, 19935426, 1,
'G53775'),
(19995918, 19995989, 1, 'G53965'), (20704664, 20704736, 1,
'G55735'),
(20720151, 20720223, 1, 'G55795'),
(20824495, 20824568, -1, 'G56085'),
(21498293, 21498375, 1, 'G58035'), (21553258, 21553329, 1,
'G58165'),
(21970486, 21970557, 1, 'G59415'), (22149699, 22149773, 1,
'G59923'),
(22149823, 22149895, -1, 'G59926'),
(22197810, 22197892, -1, 'G60075'),
(22481215, 22481288, -1, 'G60805'),
(22622384, 22622465, 1, 'G61105'), (22786896, 22786969, 1,
'G61545'),
(22853496, 22853567, 1, 'G61715'), (22871101, 22871174, 1,
'G61755'),
(22892781, 22892853, 1, 'G61825'), (23047854, 23047927, 1,
'G62245'),
(23062444, 23062517, -1, 'G62285'),
(23221682, 23221753, 1, 'G62735'),
(23296567, 23296640, -1, 'G63003'),
(23296728, 23296801, -1, 'G63006')
]
f4 = [
(33799, 33872, 1, 'G00085'), (424716, 424788, -1, 'G00985'),
(562560, 562634, -1, 'G01355'), (611865, 611932, -1, 'G01455'),
(808269, 808342, -1, 'G01865'), (901175, 901247, 1, 'G02055'),
(1390894, 1390966, 1, 'G03135'), (1442004, 1442076, 1, 'G03285'),
(1501605, 1501677, 1, 'G03405'), (1520781, 1520854, -1, 'G03435'),
(5268124, 5268210, -1, 'G08345'), (6646425, 6646496, 1, 'G10815'),
(6819287, 6819324, 1, 'G11177'), (6837555, 6837639, -1, 'G11213'),
(6837769, 6837853, -1, 'G11216'), (6905479, 6905552, -1, 'G11355'),
(6944721, 6944793, 1, 'G11405'), (7185697, 7185771, 1, 'G11985'),
(7232792, 7232865, -1, 'G12065'), (7256408, 7256481, 1, 'G12115'),
(7341420, 7341494, -1, 'G12405'), (7730956, 7731037, 1, 'G13265'),
(7814197, 7814270, 1, 'G13445'), (8255695, 8255767, 1, 'G14345'),
(8301720, 8301794, -1, 'G14415'), (8979656, 8979729, 1, 'G15775'),
(9108317, 9108391, 1, 'G16105'), (9191590, 9191663, 1, 'G16235'),
(9287230, 9287304, 1, 'G16465'), (9289706, 9289787, 1, 'G16475'),
(9815215, 9815287, -1, 'G17612'), (9873524, 9873596, -1, 'G17765'),
(9978117, 9978189, -1, 'G17975'),
(10093077, 10093157, -1, 'G18255'),
(10302011, 10302084, 1, 'G18725'),
(10325975, 10326047, -1, 'G18815'),
(10878733, 10878807, -1, 'G20115'),
(11774472, 11774508, -1, 'G22265'),
(11910299, 11910373, 1, 'G22635'),
(11954751, 11954824, -1, 'G22754'),
(11974951, 11975032, 1, 'G22785'), (12320119, 12320203, 1,
'G23635'),
(12429608, 12429681, 1, 'G23915'),
(12486211, 12486282, -1, 'G24025'),
(12686148, 12686230, 1, 'G24565'),
(13006243, 13006316, -1, 'G25435'),
(13058840, 13058922, -1, 'G25585'),
(13076582, 13076666, -1, 'G25635'),
(13285431, 13285503, -1, 'G26225'),
(13336345, 13336419, -1, 'G26375'),
(13341501, 13341575, -1, 'G26385'),
(13454562, 13454635, 1, 'G26675'),
(13704787, 13704860, 1, 'G27395'),
(13882922, 13882994, -1, 'G27875'),
(13885196, 13885269, -1, 'G27885'),
(14032495, 14032567, 1, 'G28362'), (14267286, 14267368, 1,
'G28915'),
(14470283, 14470355, 1, 'G29415'), (15120655, 15120728, 1,
'G31075'),
(15183089, 15183162, 1, 'G31265'),
(15345717, 15345753, -1, 'G31695'),
(15430229, 15430303, -1, 'G31895'),
(15576655, 15576728, 1, 'G32265'), (15671398, 15671469, 1,
'G32475'),
(15804553, 15804635, 1, 'G32765'),
(16304128, 16304201, 1, 'G34035'),
(16454700, 16454773, -1, 'G34415'),
(16556627, 16556700, 1, 'G34695'), (16655290, 16655364, 1,
'G34975'),
(17130054, 17130127, 1, 'G36197'), (17149473, 17149545, 1,
'G36245'),
(17276705, 17276779, -1, 'G36635'),
(17500800, 17500872, -1, 'G37175'),
(18254982, 18255018, -1, 'G39195'),
(18293773, 18293845, 1, 'G39345'), (18395021, 18395093, 1,
'G39615'),
(18411258, 18411332, 1, 'G39672'),
(18501705, 18501778, -1, 'G39865'),
(18542164, 18542238, 1, 'G39985')
]
f5 = [
(150353, 150426, -1, 'G01365'), (389889, 389960, -1, 'G02025'),
(508427, 508500, -1, 'G02385'), (530819, 530893, 1, 'G02435'),
(559327, 559399, -1, 'G02505'), (588890, 588964, -1, 'G02615'),
(614641, 614723, 1, 'G02725'), (642397, 642479, -1, 'G02815'),
(858534, 858571, 1, 'G03445'), (862395, 862468, -1, 'G03452'),
(970797, 970878, -1, 'G03705'), (984365, 984448, 1, 'G03745'),
(998940, 999013, 1, 'G03775'), (1742692, 1742765, 1, 'G05795'),
(1788651, 1788723, 1, 'G05945'), (1804616, 1804690, 1, 'G05985'),
(1853302, 1853382, -1, 'G06125'), (2060153, 2060235, -1, 'G06685'),
(2212678, 2212749, -1, 'G07135'), (2309512, 2309549, -1, 'G07315'),
(2411148, 2411232, 1, 'G07625'), (2432263, 2432336, -1, 'G07675'),
(2587826, 2587899, -1, 'G08075'), (2898867, 2898951, -1, 'G09345'),
(2993327, 2993401, 1, 'G09655'), (3030817, 3030890, -1, 'G09755'),
(3118377, 3118458, 1, 'G09975'), (3212351, 3212424, -1, 'G10235'),
(3287553, 3287635, -1, 'G10455'), (3324702, 3324775, 1, 'G10525'),
(3578295, 3578367, -1, 'G11225'), (3617058, 3617130, 1, 'G11325'),
(3669000, 3669073, -1, 'G11475'), (4471050, 4471122, 1, 'G13845'),
(4530475, 4530548, 1, 'G14035'), (4673902, 4673974, 1, 'G14495'),
(4929562, 4929636, 1, 'G15175'), (5157641, 5157715, 1, 'G15805'),
(5161514, 5161586, 1, 'G15815'), (5358918, 5359000, 1, 'G16375'),
(5962699, 5962771, -1, 'G18005'), (5965972, 5966044, -1, 'G18015'),
(5984378, 5984450, 1, 'G18085'), (6258146, 6258218, 1, 'G18755'),
(6401240, 6401311, 1, 'G19095'), (7073531, 7073603, -1, 'G20852'),
(7073944, 7074016, -1, 'G20854'), (7074357, 7074429, -1, 'G20856'),
(7074773, 7074845, -1, 'G20858'), (7222059, 7222131, -1, 'G21378'),
(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")
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)
#This chromosome is done
chr_diagram.add(cur_chromosome)
scale = BasicChromosome.Chromosome('Legend')
scale.scale_num = max_len + 2 * telomere_length
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)
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()
start.scale = telomere_length
cur_chromosome.add(start)
# Add a body - again using bp as the scale length here.
body = BasicChromosome.AnnotatedChromosomeSegment(length, chrom_feat)
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(snakemake.output[0], snakemake.params["title"])
logh.close()
# 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 = BasicChromosome.AnnotatedChromosomeSegment(length,feat_dict[name])
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(args.out, args.queryfasta)
#
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)
'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)
end.scale = telomere_length
group.add(end)
chr_diagram.add(group)
chr_diagram.draw(sys.argv[4], "Group for Joinmap")
strand=1)
tmp_start = region_unit * i
tmp_featur.qualifiers["locus_tag"] = str(tmp_start)
lad_feature_s.append(tmp_featur)
lad_rec.features = lad_feature_s
cur_chromosome = BasicChromosome.Chromosome(lad_rec.id)
cur_chromosome.scale_num = max_len + 2 * telomere_length
start = BasicChromosome.TelomereSegment()
start.scale = telomere_length
cur_chromosome.add(start)
feature = {}
body = BasicChromosome.AnnotatedChromosomeSegment(scale_max,
lad_rec.features)
body.scale = scale_max
cur_chromosome.add(body)
end = BasicChromosome.TelomereSegment(inverted=True)
end.scale = telomere_length
cur_chromosome.add(end)
chr_diagram.add(cur_chromosome)
####ladder 終了
####実際の配列スタート
with open(fasta_in, "r") as fh:
for record in SeqIO.parse(fh, "fasta"):
features = [] #featuresを初期化しておく(無い時があるので）
