Low-level API

Contents:

• Array operations
  • arange_multi()
  • closest_intervals()
  • interweave()
  • merge_intervals()
  • overlap_intervals()
  • overlap_intervals_outer()
  • sum_slices()
• Specifications
  • is_chrom_dtype()
  • specs._verify_column_dtypes()
  • specs._verify_columns()
  • specs._get_default_colnames()
• String operations
  • is_complete_ucsc_string()
  • parse_region()
  • parse_region_string()
  • to_ucsc_string()

Low level array-based operations are used to implement the genomic interval operations on dataframes.

import itertools

import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import pandas as pd

import bioframe as bf
import bioframe.vis


from bioframe.core import arrops

starts1, ends1 = np.array([
    [1,5],
    [3,8],
    [8,10],
    [12,14]
]).T

starts2, ends2 = np.array([
    [4,8],
    [10,11],
]).T

bf.vis.plot_intervals_arr(
    starts = starts1,
    ends = ends1,
    xlim = (-0.5,14.5),
    labels = np.arange(0,starts1.shape[0]),
    show_coords = True)

bf.vis.plot_intervals_arr(
    starts = starts2,
    ends = ends2,
    colors = 'lightpink',
    xlim = (-0.5,14.5),
    labels = np.arange(0,starts2.shape[0]),
    show_coords = True)

arrops.overlap_intervals(starts1, ends1, starts2, ends2)

array([[0, 0],
       [1, 0]])

arrops.overlap_intervals_outer(starts1, ends1, starts2, ends2)

(array([[0, 0],
        [1, 0]]),
 array([2, 3]),
 array([1]))

arrops.merge_intervals(starts1, ends1, min_dist=0)

(array([0, 0, 0, 1]), array([ 1, 12]), array([10, 14]))

arrops.merge_intervals(starts1, ends1, min_dist=None)

(array([0, 0, 1, 2]), array([ 1,  8, 12]), array([ 8, 10, 14]))

arrops.merge_intervals(starts1, ends1, min_dist=2)

(array([0, 0, 0, 0]), array([1]), array([14]))

arrops.complement_intervals(starts1, ends1)

(array([ 0, 10, 14]),
 array([                  1,                  12, 9223372036854775807]))