def template_vdom_motif_pair(main_motif,
motif_pair,
lpdata,
dfab,
profile_mapping,
figures_dir,
figures_url,
cache=False,
**kwargs):
motif_figs = []
other = motif_pair[0] if motif_pair[0] != main_motif else motif_pair[1]
# HACK - pass the tasks
for task in ['Oct4', 'Sox2', 'Nanog', 'Klf4']:
figs, dist_seq = motif_pair_figs(main_motif, task, motif_pair, lpdata,
dfab, **kwargs)
motif_figs += figs
if task == profile_mapping[main_motif]:
dist_seq_fig = dist_seq
return details(
summary(b(main_motif), f" (perturb {other})"), *[
details(
summary(k), *[
cache_fig(x,
figures_dir,
figures_url,
str(i) + "-" + main_motif + "<>" + other + "-" +
k,
width=840 if k is not "Distance" else 400,
cache=cache) for i, x in enumerate(v)
]) for k, v in dist_seq_fig + motif_figs
])
def vdm_heatmaps(seqlets,
d,
included_samples,
tasks,
pattern,
top_n=None,
pssm_fig=None,
opened=False,
resize_width=200):
ex_signal, ex_contrib_profile, ex_contrib_counts, ex_seq, sort_idx = get_signal(
seqlets, d, included_samples, tasks, resize_width=resize_width)
if top_n is not None:
sort_idx = sort_idx[:top_n]
return div(
details(summary("Sequence:"),
pssm_fig,
br(),
fig2vdom(
heatmap_sequence(ex_seq,
sort_idx=sort_idx,
figsize_tmpl=(10, 15),
aspect='auto')),
open=opened),
details(
summary("ChIP-nexus counts:"),
fig2vdom(
multiple_plot_stranded_profile(
ex_signal, figsize_tmpl=(20 / len(ex_signal), 3))),
# TODO - change
fig2vdom(
multiple_heatmap_stranded_profile(ex_signal,
sort_idx=sort_idx,
figsize=(20, 20))),
open=opened),
details(summary("Contribution scores (profile)"),
fig2vdom(
multiple_heatmap_contribution_profile(ex_contrib_profile,
sort_idx=sort_idx,
figsize=(20, 20))),
open=opened),
details(summary("Contribution scores (counts)"),
fig2vdom(
multiple_heatmap_contribution_profile(ex_contrib_counts,
sort_idx=sort_idx,
figsize=(20, 20))),
open=opened))
def template_vdom_metacluster(name,
n_patterns,
n_seqlets,
important_for,
patterns,
is_open=False):
return details(summary(
b(name), f", # patterns: {n_patterns},"
f" # seqlets: {n_seqlets}, "
"important for: ", b(important_for)),
ul([li(pattern) for pattern in patterns], start=0),
id=name,
open=is_open)
def template_vdom_pattern(name,
n_seqlets,
trimmed_motif,
full_motif,
figures_url,
add_plots={},
metacluster=""):
return details(
summary(
name,
f": # seqlets: {n_seqlets}",
# br(),
trimmed_motif), # ", rc: ", motif_rc),
details(
summary("Aggregated profiles and contribution scores)"),
img(src=figures_url + "/agg_profile_contribcores.png", width=840),
),
details(
summary("Aggregated hypothetical contribution scores)"),
img(src=figures_url + "/agg_profile_hypcontribscores.png",
width=840),
),
details(
summary("Sequence"),
full_motif,
br(),
img(src=figures_url + "/heatmap_seq.png", width=840 // 2),
),
details(
summary("ChIP-nexus counts"),
img(src=figures_url + "/profile_aggregated.png", width=840),
img(src=figures_url + "/profile_heatmap.png", width=840),
),
details(
summary("Importance scores (profile)"),
img(src=figures_url + "/contrib_profile.png", width=840),
),
details(
summary("Importance scores (counts)"),
img(src=figures_url + "/contrib_counts.png", width=840),
),
*[details(summary(k), *v) for k, v in add_plots.items()],
id=metacluster + "/" + name)