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Description:

IRanges 0.2.11

Integer ranges in Python
Python implementation of the IRanges Bioconductor package.
To get started, install the package from PyPI
pip install iranges

# To install optional dependencies
pip install iranges[optional]

IRanges
An IRanges holds a start position and a width, and is most typically used to represent coordinates along some genomic sequence. The interpretation of the start position depends on the application; for sequences, the start is usually a 1-based position, but other use cases may allow zero or even negative values.
from iranges import IRanges

starts = [1, 2, 3, 4]
widths = [4, 5, 6, 7]
x = IRanges(starts, widths)

print(x)

## output
IRanges object with 4 ranges and 0 metadata columns
start end width
<ndarray[int32]> <ndarray[int32]> <ndarray[int32]>
[0] 1 5 4
[1] 2 7 5
[2] 3 9 6
[3] 4 11 7

Interval Operations
IRanges supports most interval based operations. For example to compute gaps
x = IRanges([-2, 6, 9, -4, 1, 0, -6, 10], [5, 0, 6, 1, 4, 3, 2, 3])

gaps = x.gaps()
print(gaps)

## output

IRanges object with 2 ranges and 0 metadata columns
start end width
<ndarray[int32]> <ndarray[int32]> <ndarray[int32]>
[0] -3 -2 1
[1] 5 9 4

Or Perform interval set operations
x = IRanges([1, 5, -2, 0, 14], [10, 5, 6, 12, 4])
y = IRanges([14, 0, -5, 6, 18], [7, 3, 8, 3, 3])

intersection = x.intersect(y)
print(intersection)

## output
IRanges object with 3 ranges and 0 metadata columns
start end width
<ndarray[int32]> <ndarray[int32]> <ndarray[int32]>
[0] -2 3 5
[1] 6 9 3
[2] 14 18 4

Overlap operations
IRanges uses nested containment lists under the hood to perform fast overlap and search based operations. These methods typically return a list of indices that map to each interval in query.
subject = IRanges([2, 2, 10], [1, 2, 3])
query = IRanges([1, 4, 9], [5, 4, 2])

overlap = subject.find_overlaps(query)
print(overlap)

## output
[[1, 0], [], [2]]

Similarly one can perform search operations like follow, precede or nearest.
query = IRanges([1, 3, 9], [2, 5, 2])
subject = IRanges([3, 5, 12], [1, 2, 1])

nearest = subject.nearest(query, select="all")
print(nearest)

## output
[[0], [0, 1], [2]]

Further Information

IRanges reference
Bioc/IRanges

Note
This project has been set up using PyScaffold 4.5. For details and usage
information on PyScaffold see https://pyscaffold.org/.