NB: This package is deprecated. Please, use the
intervaltree
package instead (available via Github or PyPI).The genome-related functionality is extracted to the
intervaltree-bio
package (Github, PyPI).No future versions of this package are planned. Do not file issues.
A mutable, self-balancing interval tree. Queries may be by point, by range overlap, or by range envelopment.
This library was designed to allow tagging text and time intervals, where the intervals include the lower bound but not the upper bound.
The easiest way to install most Python packages is via easy_install
or pip
:
$ pip install PyIntervalTree
- Initialize blank or from an iterable of Intervals in O(n * log n).
- Insertions
tree[begin:end] = data
tree.add(interval)
tree.addi(begin, end, data)
tree.extend(list_of_interval_objs)
- Deletions
tree.remove(interval)
(raisesValueError
if not present)tree.discard(interval)
(quiet if not present)tree.removei(begin, end, data)
tree.discardi(begin, end, data)
tree.remove_overlap(point)
tree.remove_overlap(begin, end)
(removes all overlapping the range)tree.remove_envelop(begin, end)
(removes all enveloped in the range)
- Overlap queries:
tree[point]
tree[begin:end]
tree.search(point)
tree.search(begin, end)
- Envelop queries:
tree.search(begin, end, strict = True)
- Membership queries:
interval_obj in tree
(this is fastest, O(1))tree.containsi(begin, end, data)
tree.overlaps(point)
tree.overlaps(begin, end)
- Iterable:
for interval_obj in tree:
tree.items()
- Sizing:
len(tree)
tree.is_empty()
not tree
tree.begin()
(the smallest coordinate of the leftmost interval)tree.end()
(theend
coordinate of the rightmost interval)
- Restructuring
split_overlaps()
- Copy- and typecast-able:
IntervalTree(tree)
(Interval
objects are same as those in tree)tree.copy()
(Interval
objects are shallow copies of those in tree)set(tree)
(can later be fed intoIntervalTree()
)list(tree)
(ditto)
- Equal-able
- Pickle-friendly
- Automatic AVL balancing
Getting started:
from intervaltree import Interval, IntervalTree t = IntervalTree()
Adding intervals - you don't have to use strings!:
t[1:2] = "1-2" t[4:7] = "4-7" t[5:9] = "5-9"
Query by point:
ivs = t[6] # set([Interval(4, 7, '4-7'), Interval(5, 9, '5-9')]) iv = sorted(ivs)[0] # Interval(4, 7, '4-7')
Accessing an
Interval
object:iv.begin # 4 iv.end # 7 iv.data # "4-7"
Query by range:
Note that ranges are inclusive of the lower limit, but non-inclusive of the upper limit. So:
t[2:4] # set([])
But:
t[1:5] # set([Interval(1, 2, '1-2'), Interval(4, 7, '4-7')])
Constructing from lists of
Interval
's:We could have made the same tree this way:
ivs = [ [1,2], [4,7], [5,9] ] ivs = map( lambda begin,end: Interval(begin, end, "%d-%d" % (begin,end), *zip(*ivs) ) t = IntervalTree(ivs)
Removing intervals:
t.remove( Interval(1, 2, "1-2") ) list(t) # [Interval(4, 7, '4-7'), Interval(5, 9, '5-9')] t.remove( Interval(500, 1000, "Doesn't exist") # raises ValueError t.discard(Interval(500, 1000, "Doesn't exist") # quietly does nothing t.remove_overlap(5) list(t) # []
We could also empty a tree by removing all intervals, from the lowest bound to the highest bound of the
IntervalTree
:t.remove_overlap(t.begin(), t.end())
Interval trees are especially commonly used in bioinformatics, where intervals correspond to genes or various features along the genome. Such intervals are commonly stored in BED
-format files. To simplify working with such data, the package intervaltree.bio
provides a GenomeIntervalTree
class.
GenomeIntervalTree
is essentially a dict
of IntervalTree
-s, indexed by chromosome names:
gtree = GenomeIntervalTree() gtree['chr1'].addi(10000, 20000)
There is a convenience function for adding intervals:
gtree.addi('chr2', 20000, 30000)
You can create a GenomeIntervalTree
instance from a BED
file:
test_url = 'http://hgdownload.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeAwgTfbsUniform/wgEncodeAwgTfbsBroadDnd41Ezh239875UniPk.narrowPeak.gz' data = zlib.decompress(urlopen(test_url).read(), 16+zlib.MAX_WBITS) gtree = GenomeIntervalTree.from_bed(StringIO(data))
In addition, special functions are offered to read in UCSC tables of gene positions:
Load the UCSC
knownGene
table with each interval corresponding to gene's transcribed region:knownGene = GenomeIntervalTree.from_table()
Load the UCSC
refGene
table with each interval corresponding to gene's coding region:url = 'http://hgdownload.cse.ucsc.edu/goldenpath/hg19/database/refGene.txt.gz' refGene = GenomeIntervalTree.from_table(url=url, parser=UCSCTable.REF_GENE, mode='cds')
Load the UCSC
ensGene
table with each interval corresponding to a gene's exon:url = 'http://hgdownload.cse.ucsc.edu/goldenpath/hg19/database/ensGene.txt.gz' ensGene = GenomeIntervalTree.from_table(url=url, parser=UCSCTable.ENS_GENE, mode='exons')
You may add methods for parsing your own tabular files with genomic intervals, see the documentation for GenomeIntervalTree.from_table
.
- Eternally Confuzzled's AVL tree
- Wikipedia's Interval Tree
- Heavily modified from Tyler Kahn's Interval Tree implementation in Python (GitHub project)
- Chaim-Leib Halbert
- This particular fork by Konstantin Tretyakov. See changes in CHANGELOG.txt.