def aggregate_by_tad(all_TADs_by_celltype,
aggregations,
other,
extension=0.1,
n_windows=100):
tot_windows = n_windows + int(n_windows * extension) * 2
tad_start_window = int(n_windows * extension)
tad_end_window = n_windows + int(n_windows * extension)
regions = all_TADs_by_celltype[coords + ['tad_uid']].copy()
regions['tad_uid'] = regions.tad_uid.map(lambda x: x.replace("_", "-"))
windows = BedTool().window_maker(b=BedTool.from_dataframe(regions)\
.slop(l=extension, r=extension,
pct=True, genome="hg19"),
n=tot_windows, i='srcwinnum')\
.to_dataframe(names=coords + ['window_uid'])
windows_idxs = windows.window_uid.str.split("_", expand=True)
windows_idxs.columns = ['tad_uid', 'win_num']
windows = pd.concat((windows, windows_idxs), axis=1)
windows['win_num'] = windows['win_num'].astype(int)
windows = windows.sort_values(coords).reset_index(drop=True)
windows_with_ctcfs = coverage_by_window(windows, other, aggregations)
aggregations_by_tad = {}
for c in aggregations.keys():
print(" " * 100, end='\r')
print(c, end="\r")
cagg = windows_with_ctcfs.pivot_table(index='tad_uid',
columns='win_num',
values=c).sort_index(axis=1)
cagg = cagg.sort_index(axis=1)
aggregations_by_tad[c] = cagg
return aggregations_by_tad, tad_start_window, tad_end_window
def windowing_by_number(all_TADs_by_celltype, n_windows):
windows = BedTool().window_maker(b=BedTool.from_dataframe(all_TADs_by_celltype),
n=n_windows, i='srcwinnum')\
.to_dataframe(names=all_TADs_by_celltype.columns.tolist())
idxs = windows[all_TADs_by_celltype.columns[-1]].str.split("_", expand=True)
tad_ids = idxs.iloc[:, :-1].apply(lambda x: "_".join(x), axis=1)
w_nums = idxs.iloc[:, -1].astype(int) - 1
windows[all_TADs_by_celltype.columns[-1]] = tad_ids
windows['w_num'] = w_nums
windows = windows.sort_values(coords).reset_index(drop=True)
return windows
def windowing_by_size(centered_boundaries, window_size):
windows = BedTool().window_maker(b=BedTool.from_dataframe(centered_boundaries),
w=window_size, i='srcwinnum')\
.to_dataframe(names=centered_boundaries.columns.tolist())
idxs = windows[centered_boundaries.columns[-1]].str.split("_", expand=True)
tad_ids = idxs.iloc[:, :-1].apply(lambda x: "_".join(x), axis=1)
w_nums = idxs.iloc[:, -1].astype(int) - 1
windows[centered_boundaries.columns[-1]] = tad_ids
windows['w_num'] = w_nums
windows = windows.sort_values(coords).reset_index(drop=True)
return windows