anhima.loc
- Locating variants, samples and genome regions¶import numpy as np
np.random.seed(1)
import random
random.seed(1)
import matplotlib.pyplot as plt
%matplotlib inline
import sys
import anhima
# dev imports
# sys.path.insert(0, '../src')
# %load_ext autoreload
# %autoreload 1
# %aimport anhima.ld
# %aimport anhima.loc
# simulate non-uniform variant positions
n_variants = 1000
p = 0
pos = []
for i in range(n_variants):
gap = int(np.abs(np.cos(i/100))*100)
p += gap
pos.append(p)
pos = np.array(pos)
# plot variant locations
anhima.loc.plot_variant_locator(pos, step=10);
# plot variant locations with y axis inverted
anhima.loc.plot_variant_locator(pos, step=10, flip=True);
loc = anhima.loc.locate_region(pos, 11000, 20000)
loc
slice(118, 305, None)
pos[loc.start-1], pos[loc.start]
(10972, 11026)
pos[loc.stop-1], pos[loc.stop]
(19990, 20088)
# plot variant counts
anhima.loc.plot_windowed_variant_counts(pos, window_size=1000);
# plot variant counts
anhima.loc.plot_windowed_variant_counts(pos, window_size=5000);
# plot variant density
anhima.loc.plot_windowed_variant_density(pos, window_size=1000);
# plot variant density
anhima.loc.plot_windowed_variant_density(pos, window_size=5000);