def findseq():
gpath = config.root
mycgbk = os.path.join(gpath, 'genomes/Bacteria/Mycoplasma_mycoides_SC_PG1_uid58031/NC_005364.gbk')
mycfa = os.path.join(gpath, 'genomes/Bacteria/Mycoplasma_mycoides_SC_PG1_uid58031/NC_005364.fna')
grec = SeqIO.parse(mycgbk, 'genbank')
frec = SeqIO.parse(mycfa, 'fasta')
fa = list(frec)[0]
grecf0 = list(grec)[0].features
grecf = it.ifilter(lambda x: 'gene' in x.qualifiers.keys(), grecf0)
grecf = sorted(list(grecf), key = lambda x:x.qualifiers['gene'])
geneproducts = {}
for key, grp in it.groupby(grecf, lambda x : x.qualifiers['gene']):
g = list(grp)
print key, len(g)
for k in key:
geneproducts[k] = g
lens = map(lambda x: len(x), geneproducts.values())
loc = lambda x: [x.location.start.position, x.location.end.position]
expand = lambda x, y: [np.min(x[0],y[0]), np.max(x[1],y[1])]
nprods = len(geneproducts.keys())
import compbio.utils.colors
colors = utils.colors.getct(nprods)
cshow = range(10)
clam = lambda x: x in cshow and colors[x] or [1,0,0]
f = plt.figure(0)
f.clear()
ax = f.add_subplot(111)
rs, cs = [],[]
ct = 0
#utils.plots.spacefill(ax, rs, cs)
import compbio.utils.hilbert as h
speed_hash = h.gInterp(grecf0)
#levs = h.inverseN(len(rs))
bert = h.Hilbert(5, angle = 90)
all_verts = bert.vertices(0,1)
ax.plot(all_verts[:,0],
all_verts[:,1],
color = 'black',
alpha = .1)
src = list(it.ifilter(lambda x: x.type =='source',grecf0))[0]
src_pos = [src.location.start.position,
src.location.end.position]
genome_l = src_pos[1] - src_pos[0]
for i in range(len(geneproducts.keys())):
g=geneproducts.values()[i]
for elt in g:
if elt.type == 'CDS':
r = array([elt.location.start.position , elt.location.end.position],float)
fracs = [speed_hash[r[0]],speed_hash[r[1]]]
verts = bert.vertices(fracs[0],fracs[1],snap = False)
ax.plot(verts[:,0],verts[:,1],
color = clam(i),
linewidth = 8)
raise Exception()
def maptRNAs(gbkfile, ax = None):
grec = SeqIO.parse(gbkfile, 'genbank')
grec = list(grec)[0].features
blank_speedfun = lambda x :\
x.type == 'tRNA' and 2 \
or x.type == 'gene' and 2 \
or x.type == 'CDS' and 2 \
or 0
speedfun = lambda x :\
x.type == 'tRNA' and 5000 \
or x.type == 'gene' and 1 \
or x.type == 'CDS' and 5 \
or 0
global funtype
if functype == 'speed':
speed_hash = h.gInterp(grec,speedfun)
else:
speed_hash = h.gInterp(grec,blank_speedfun)
global lvls
bert = h.Hilbert(lvls, angle = 90)
color_lam = lambda x: x.type =='tRNA' and 'red' \
or x.type =='CDS' and 'blue' \
or 'none'
z_lam = lambda x: x.type =='tRNA' and '1' \
or 0
width_lam = lambda x: x.type =='tRNA' and 8 \
or 16
alpha_lam = lambda x: x.type =='tRNA' and 1 \
or .5
if not ax:
f = plt.figure(0)
f.clear()
ax = f.add_axes([0,0,1,1], xlim = [-.2,1.2],
ylim = [-.2,1.2])
from matplotlib.collections import LineCollection as lc
v0 = bert.vertices(0,1)
ax.plot(v0[:,0], v0[:,1], color = 'black', alpha = .2)
global tcols
global tct
for r in grec:
if r.type != 'tRNA':
continue
p = r.qualifiers['product'][0]
aa = re.search(re.compile('-(.*)'), p).group(1)
if not aa in tcols.keys():
tcols[aa] = tct.pop()
print tcols['Phe']
for r in grec:
if not (r.type == 'gene' or r.type =='CDS' or r.type == 'tRNA'):
continue
color = 'none'
if r.type == 'tRNA':
p = r.qualifiers['product'][0]
aa = re.search(re.compile('-(.*)'), p).group(1)
color = tcols[aa]
if r.type == 'gene' or r.type == 'CDS':
rec = r
string = rec.__str__()
for k, v in tcols.iteritems():
if k in string and (not k in ['Val','Pro']) :
color = v
if 'ynthetase' in string:
color = 'black'
if color == 'none':
continue
#color = color_lam(r)
alpha = alpha_lam(r)
width = width_lam(r)
z = z_lam(r)
l0 = r.location.start.position
l1 = r.location.end.position
fracs = speed_hash[l0],speed_hash[l1]
verts = bert.vertices(fracs[0],fracs[1], snap = False)
ax.plot(verts[:,0], verts[:,1],
color = color,
linewidth = width,
alpha = alpha,
zorder = z)
