def getBetweenHeter(cool, chrom_heter_pairs, method='median'):
method_func = np.median if method == 'median' else np.mean
contact_data = []
hm = cool2matrix(cool)
for chrom_pair in chrom_heter_pairs:
chrom1, chrom2 = chrom_pair
chrom_hm = getChromPairsMatrix(cool, hm, chrom1, chrom2)
contact_data.extend(method_func(chrom_hm, axis=1))
return contact_data
def getBetweenHomo(cool, chrom_homo_pairs, method='median'):
method_func = np.median if method == 'median' else np.mean
contact_data = []
hm = cool2matrix(cool)
for homo_chroms in chrom_homo_pairs:
chrom_pairs = list(combinations(homo_chroms, 2))
for chrom_pair in chrom_pairs:
chrom1, chrom2 = chrom_pair
chrom_hm = getChromPairsMatrix(cool, hm, chrom1, chrom2)
contact_data.extend((method_func(chrom_hm, axis=1)))
return contact_data
def getWithinChromosome(cool, method='median'):
method_func = np.median if method == 'median' else np.mean
chroms = cool.chromnames
hm = cool2matrix(cool)
contact_data = []
for chrom in chroms:
idx = cool.bins().fetch(chrom).index
start = idx[0]
end = idx[-1]
contact_mean_data = method_func(hm[start:end + 1, start:end + 1],
axis=1)
contact_data.extend(contact_mean_data)
return contact_data
def main(args):
p = p = argparse.ArgumentParser(prog=__file__,
description=__doc__,
conflict_handler='resolve')
pReq = p.add_argument_group('Required arguments')
pOpt = p.add_argument_group('Optional arguments')
pReq.add_argument('-m',
'--matrix',
required=True,
help='contact matrix with cool formats')
pOpt.add_argument('-o', '--output', help='output of picture')
pOpt.add_argument(
'--method',
choices=['average', 'median'],
default='median',
help='method of interaction frequency per bin [default: %(default)s]')
pOpt.add_argument('-h',
'--help',
action='help',
help='show help message and exit.')
args = p.parse_args(args)
output = args.matrix.rsplit('.', 1)[0] + '_TransInteractionWithinHomo_boxplot.pdf' \
if not args.output else args.output
method_func = np.median if args.method == 'median' else np.mean
cool = cooler.Cooler(args.matrix)
resolution_string = chrom_size_convert(cool.binsize)
all_chroms = cool.chromnames
chrom_heter_pairs = list(
filter(is_heter, list(combinations(all_chroms, 2))))
homo_chroms = sorted(set(map(lambda x: x[:-1], cool.chromnames)))
chrom_homo_pairs = find_homo_chrom(homo_chroms, all_chroms)
hm = cool2matrix(cool)
boxprops = dict(color='black', linewidth=1.5)
medianprops = dict(color='black', linewidth=2.5)
whiskerprops = dict(linestyle='--')
fig, axes = plt.subplots(2, 4, figsize=(8, 4.5), sharey=True)
plt.subplots_adjust(hspace=0.45)
axes_list = [ax for ax_row in axes for ax in ax_row]
data = []
for i, chroms in enumerate(chrom_homo_pairs):
chr_data = []
chrom_pairs = list(permutations(chroms, 2))
homo_data = []
for chrom in chroms:
haps = (list(filter(lambda x: x[0] == chrom, chrom_pairs)))
haps_data = []
for chrom_pair in haps:
chrom1, chrom2 = chrom_pair
chrom_matrix = getChromPairsMatrix(cool, hm, chrom1, chrom2)
chrom_matrix.sort(axis=1)
haps_data.extend(method_func(chrom_matrix, axis=1))
homo_data.append(haps_data)
# homo_data.append(getChromPairsMatrix(cool, hm, chrom_pair[0], chrom_pair[1]))
ax = axes_list[i]
bplot = ax.boxplot(homo_data,
showfliers=False,
patch_artist=True,
notch=True,
widths=0.35,
medianprops=medianprops,
whiskerprops=whiskerprops,
boxprops=boxprops)
for patch, color in zip(bplot['boxes'],
['#a83836', '#275e8c', '#df8384', '#8dc0ed']):
patch.set_facecolor(color)
ax.set_xticklabels(chroms, rotation=45)
fig.text(
0.02,
0.5,
"Interaction Frequency\n(contacts / {})".format(resolution_string),
rotation=90,
va='center')
plt.savefig(output, dpi=300, bbox_inches='tight')
plt.savefig(output.rsplit('.', 1)[0] + '.png',
dpi=300,
bbox_inches='tight')
def plotCisTrans(args):
"""
%(prog)s <coolfile> [coolfile ...] [Options]
calculate the cis and trans interaction, and plot the barplot.
"""
p = argparse.ArgumentParser(prog=plotCisTrans.__name__,
description=plotCisTrans.__doc__,
conflict_handler='resolve')
pReq = p.add_argument_group('Required arguments')
pOpt = p.add_argument_group('Optional arguments')
pReq.add_argument('cool', nargs='+',
help='cool file of hicmatrix')
pOpt.add_argument('--sample', nargs='+',
help='sample name of each cool file [default: coolprefix]', )
pOpt.add_argument('--perchr', action='store_true', default=False,
help='plot cis/trans ration per chromosome [default: %(default)]')
pOpt.add_argument('--hideLegend', action='store_true', default=False,
help='hide legend label [default: %(default)s]')
pOpt.add_argument('--colors', nargs="*", default=None,
help='colors of bar [default: %(default)s]')
pOpt.add_argument('-o', '--outprefix', default='out',
help='out prefix of output picture and result [default: %(default)]')
pOpt.add_argument('-h', '--help', action='help',
help='show help message and exit.')
args = p.parse_args(args)
outprefix = args.outprefix
cis_list = []
trans_list = []
for coolfile in args.cool:
cool = cooler.Cooler(coolfile)
hm = cool2matrix(cool)
# calculate cis counts
counts = np.zeros(cool.info['nbins'])
for chrom in cool.chromnames:
idx = cool.bins().fetch(chrom).index
counts[idx] = np.triu(hm[idx][:, idx]).sum(axis=1)
cis_list.append(int(counts.sum()))
## calculate trans counts
counts = np.zeros(cool.info['nbins'])
for chrom in cool.chromnames:
idx = cool.bins().fetch(chrom).index
start = idx[0]
end = idx[-1]
hm[start: end + 1, start: end + 1] = 0
counts[idx] = hm[idx].sum(axis=1)
counts = counts / 2
trans_list.append(int(counts.sum()))
#print(counts.sum())
if len(cis_list) == 1 and len(trans_list) == 1:
cis, trans = cis_list[0], trans_list[0]
fig, ax = plt.subplots(figsize=(2.8, 4))
ax.bar([1.1, 2], [cis, trans], width=.6, align='center',
color=['#ffa040', '#55a0fb'], edgecolor='#606060',
linewidth=2)
ax.set_xticks([1, 2])
ax.set_xlim(0.5, 2.5)
ax.set_ylim(0, max([cis, trans]) * 1.2)
ax.set_xticklabels(['${cis}$', '${trans}$'], fontsize=14)
ax.set_ylabel('Contact probability', fontsize=15)
ax.tick_params(axis='both', which='major', labelsize=14,)
ax.tick_params(axis='x', which='major', width=0)
ax.tick_params(axis='y', which='major', width=2, length=5)
ax.spines['left'].set_linewidth(2)
ax.spines['bottom'].set_linewidth(0)
ax.ticklabel_format(axis='y', style='sci', scilimits=(0, 0), useMathText=True)
sns.despine()
outpdf = outprefix + "_cis_trans.pdf"
outpng = outprefix + "_cis_trans.png"
plt.savefig(outpdf, bbox_inches='tight', dpi=300)
plt.savefig(outpng, bbox_inches='tight', dpi=300)
logging.debug("Successful plotting total cis trans barplot in `{}`".format(outpdf))
output = outprefix + "_cis_trans.tsv"
## output total cis and trans counts
with open(output, 'w') as out:
print("Cis", end='\t', file=out)
print('\t'.join(map(str, cis_list)), file=out)
print("Trans", end='\t', file=out)
print('\t'.join(map(str, trans_list)), file=out)
logging.debug("Output total cis and trans count to `{}`".format(output))
plt.close() ## close plt
## plotting per chromosome cis/trans ratio barplot
if args.perchr:
if not args.sample:
samples = list(map(lambda x: x.split(".")[0], args.cool))
else:
samples = args.sample
if len(samples) != len(args.cool):
logging.error('cool must equal sample')
legend = False if args.hideLegend else True
colors = args.colors if args.colors else None
data = concatCisTransData(args.cool, samples)
outtsv = outprefix + "_cis_trans_ratio_perchr.tsv"
data.to_csv(outtsv, sep='\t', header=None, index=None)
logging.debug("Successful outputting cis/trans ratio data to `{}`".format(outtsv))
ax = plotCisTransPerChrom(data, legend=legend)
outpdf = outprefix + "_cis_trans_ratio_perchr.pdf"
outpng = outprefix + "_cis_trans_ratio_perchr.png"
plt.savefig(outpdf, bbox_inches='tight', dpi=300)
plt.savefig(outpng, bbox_inches='tight', dpi=300)
logging.debug("Successful plotting cis/trans ratio per chrom barplot in `{}`".format(outpdf))