IRanges 0.7.2
Python implementation of the [**IRanges**](https://bioconductor.org/packages/IRanges) Bioconductor package.
License: MIT
Requires Python: >=3.9

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# Integer ranges in Python

Python implementation of the [**IRanges**](https://bioconductor.org/packages/IRanges) Bioconductor package.

To get started, install the package from [PyPI](https://pypi.org/project/IRanges/)

```bash
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.

> [!NOTE]
> `ends` are expected to be inclusive to be consistent with Bioconductor representations. If they are not, we recommend subtracting 1 from the `ends`.

```python
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                4                4
     [1]                2                6                5
     [2]                3                9                6
     [3]                4               10                7

## Interval Operations

`IRanges` supports most interval based operations. For example to compute gaps

```python

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               -3                1
     [1]                5                8                4

Or Perform interval set operations

```python
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                2                5
     [1]                6                9                3
     [2]               14               17                4

### Overlap operations

IRanges uses [LTLA/nclist-cpp](https://github.com/LTLA/nclist-cpp) under the hood to perform fast overlap and search based operations. These methods typically return a hits-like BiocFrame.

```python
subject = IRanges([2, 2, 10], [1, 2, 3])
query = IRanges([1, 4, 9], [5, 4, 2])

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

     ## output
     BiocFrame with 3 rows and 2 columns
               self_hits       query_hits
          <ndarray[int64]> <ndarray[int64]>
     [0]                1                0
     [1]                0                0
     [2]                2                2

Similarly one can perform search operations like follow, precede or nearest.

```python
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
     BiocFrame with 4 rows and 2 columns
               query_hits        self_hits
          <ndarray[int64]> <ndarray[int64]>
     [0]                0                0
     [1]                0                1
     [2]                1                1
     [3]                2                2

## Further Information

- [IRanges reference](https://biocpy.github.io/IRanges/api/iranges.html#iranges-package)
- [Bioc/IRanges](https://bioconductor.org/packages/release/bioc/html/IRanges.html)


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## Note

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