kla_only_no_p65 = sum((gr_group['gr_dex_tag_count'] <= min_tags) &
(gr_group['gr_kla_dex_tag_count'] > min_tags) &
(gr_group['p65_kla_tag_count'] + gr_group['p65_kla_dex_tag_count'] <= min_tags)
)
counts = [tethered, direct_comp_gr, indirect_comp_gr,
direct_comp_p65, cobound,
direct_novel, indirect_novel,
in_dex_no_p65, kla_only_no_p65]
else: counts = [0]*9
stats = stats + counts
all_stats.append(dict(zip(labels, stats))), index.append(group.name)
grouped.apply(count_enhancers)
# There must be a better way to do this group-apply, but I can't make it turn back into a DF...
enhancer_counts = DataFrame(all_stats, index=index)
spaced_labels = ['\n'.join(map(' '.join,
[l.split()[i:i+2] for i in xrange(0,len(l.split()),2)] ))
for l in labels]
erna_title = 'Enhancers per Gene by enhancer subtype {0}'.format(name)
ax = yzer.boxplot([enhancer_counts[col] for col in labels], spaced_labels,
title=erna_title,
xlabel='Subset',
ylabel='Count',
show_outliers=False, show_plot=False, wide=True
)
yzer.ylim(ax, -1, 2)
pyplot.setp(ax.get_xticklabels(), fontsize=10)
yzer.save_plot(yzer.get_filename(img_dirpath, erna_title + '.png'))
yzer.show_plot()
counts,
labels,
title='Enhancer-like Subsets {0} with GR\nby Putative Mechanism'
.format(name.title()),
small_legend=True,
save_dir=img_dirpath,
show_plot=True)
enh_change = [d['dex_over_kla_1_lfc'] for d in [data, dataset] + sets]
change_labels = ['All Enhancer-like', 'All {0}'.format(name)] + labels
change_labels = [
'\n'.join(
map(' '.join,
[l.split()[i:i + 2]
for i in xrange(0, len(l.split()), 2)]))
for l in change_labels
]
erna_title = 'eRNA Change by enhancer subtype {0}- KLA+Dex versus KLA'.format(
name)
ax = yzer.boxplot(enh_change,
change_labels,
title=erna_title,
xlabel='Subset',
ylabel='log2(KLA+Dex GRO-seq/KLA GRO-seq)',
show_outliers=False,
show_plot=False,
wide=True)
yzer.ylim(ax, -4, 2)
pyplot.setp(ax.get_xticklabels(), fontsize=10)
yzer.save_plot(yzer.get_filename(img_dirpath, erna_title + '.png'))
yzer.show_plot()
ctl_y,
'o-',
color='black',
label='Control (n=8)',
linewidth=8)
pyplot.plot(low_x,
low_y,
'o-',
color='blue',
label='Low Dose TDB (107 ug, n=4)',
linewidth=6)
pyplot.plot(med_x,
med_y,
'o--',
color='green',
label='Medium Dose TDB (214 ug, n=4)',
linewidth=6)
pyplot.plot(high_x,
high_y,
'o--',
color='red',
label='High Dose TDB (321 ug, n=4)',
linewidth=4)
pyplot.legend(loc='lower left')
pyplot.xticks(x_vals, x_labels)
yzer.ylim(ax, 0, 100)
yzer.xlim(ax, 0, max(x_vals))
yzer.save_plot_with_dir(img_dirpath, None, title)
yzer.show_plot()
