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(c) MGH Center for Integrated Diagnostics
"""
from __future__ import print_function
from __future__ import absolute_import
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import colors
import matplotlib.collections as collections
import pandas as pd
from pyensembl import EnsemblRelease
from math import ceil
__author__ = 'Allison MacLeay'
class CoverageViz(object):
"""Creates a coverage bar chart and highlights exons """
def __init__(self, chrom, start, stop, hist, metaval=None):
self.chrom = chrom
self.start = start
self.stop = stop
self.dict = self._to_dict(hist) # hist is [x, y] where x is position and y is coverage
self.hist = self.xy()
self.metaval = '{}\n'.format(metaval) if metaval else ''
def _to_dict(self, hist):
""" pad coverage data to match length of region """
dct = {}
for i, pos in enumerate(hist[0]):
dct[pos] = hist[1][i]
return dct
def xy(self):
""" return array of buffered x and y"""
x, y = [], []
for i in range(self.start, self.stop):
x.append(i)
y.append(self.dict.get(i, 0))
return [x, y]
def plot(self, saveto=False):
""" Create plot """
lhist = len(self.hist[0])
plt.subplot(2, 1, 1)
n, fracs, patches = plt.hist(self.invert(), bins=lhist/10)
plt.title('ALK coverage')
plt.ylabel('colored histogram')
# We'll color code by height, but you could use any scalar
fracs = n / n.max()
# we need to normalize the data to 0..1 for the full range of the colormap
norm = colors.Normalize(fracs.min(), fracs.max())
# Now, we'll loop through our objects and set the color of each accordingly
for thisfrac, thispatch in zip(fracs, patches):
color = plt.cm.viridis(norm(thisfrac))
thispatch.set_facecolor(color)
barplot_sp = plt.subplot(2, 1, 2)
self.exon_plot(plt, barplot_sp)
if saveto:
plt.savefig(saveto)
print('Plot saved to {}'.format(saveto))
plt.show()
def exon_plot(self, plt, subplot):
_ = plt.bar(self.hist[0], self.hist[1])
exon_array, exon_df = self.parse_ref_exons()
ymax = max(self.hist[1])
coll = collections.BrokenBarHCollection.span_where(self.hist[0], ymin=0, ymax=ymax, where=exon_array > 0,
color='#41e0c8')
subplot.add_collection(coll)
plt.xticks(np.arange(self.start, self.stop, 1000))
plt.xlabel('position')
plt.ylabel('{}coverage'.format(self.metaval))
factor = ceil(float(ymax) / 7)
for i, row in exon_df.iterrows():
offset = factor + (i % 2) * factor
plt.text(row['start'], ymax - offset, 'exon {}'.format(row['number']), color='#e04641')
def invert(self):
iv = []
for i, a in enumerate(self.hist[0]):
for x in range(self.hist[1][i]):
iv.append(a + self.start)
return iv
def load_ensembl_ref(self, ens_db, version, rid=None):
""" Download, load, and index ensembl data """
ens_db.download(version)
ens_db.index()
if rid is not None:
return ens_db.transcript_by_id(rid)
else:
return None
def get_exon_numbers(self, ens_db, gene):
""" This creates exon areas
, but the numbering is off """
dct = {'start': [], 'id': []}
gene_id = ens_db.gene_ids_of_gene_name(gene)[0]
transcripts = ens_db.transcript_ids_of_gene_id(gene_id)
longest = 0
e = None
for t in transcripts:
tsc = ens_db.exon_ids_of_transcript_id(t)
sz = len(tsc)
if sz > longest:
longest = sz
e = tsc
for exid in e:
exon = ens_db.exon_by_id(exid)
dct['start'].append(exon.start)
dct['id'].append(exid)
df = pd.DataFrame(dct)
df['number'] = df.index + 1
return df
def parse_ref_exons(self):
""" Return fasta reference with only the sequences needed"""
ens_db = EnsemblRelease(75)
try:
exons = ens_db.exons_at_locus(self.chrom, self.start, self.stop)
except ValueError as e:
# Load pyensembl db
raise e
exon_array = np.zeros(self.stop - self.start)
exon_numbers = self.get_exon_numbers(ens_db, exons[0].gene_name)
for exobj in exons:
start = exobj.start - self.start
stop = exobj.end - self.start
i = start
while i < stop:
exon_array[i] = 1
i += 1
# 2:29,448,326-29,448,432 exon 19
# exon 22 start: 29445210
# exon 18 end: 29449940
# intron 19: 29446395-29448326
# ATI initiation 29446768-29448326
return exon_array, exon_numbers[(exon_numbers['start'] > self.hist[0][0]) &
(exon_numbers['start'] < self.hist[0][-1])]
class VizList(object):
def __init__(self, vizlist):
self.vizlist = vizlist
def report(self, output_file):
nsub = len(self.vizlist)
fig = plt.figure(figsize=[24, 20])
for i, viz in enumerate(self.vizlist):
sub = fig.add_subplot(nsub, 1, i + 1)
viz.exon_plot(plt, sub)
fig.tight_layout()
fig.savefig(output_file)
fig.show()
pass
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