Unit tests

GenomicRanges

GenomicRanges provides container classes designed to represent genomic locations and support genomic analysis. It is similar to Bioconductor's GenomicRanges. Intervals are inclusive on both ends and starts at 1.

Note: V0.4.0 is a complete overhaul of the package, as such the constructor to GenomicRanges has changed!

To get started, install the package from PyPI

pip install genomicranges

`GenomicRanges`

GenomicRanges is the base class to represent and operate over genomic regions and annotations.

From UCSC or GTF file

You can easily download and parse genome annotations from UCSC or load a genome annotation from a GTF file,

import genomicranges

gr = genomicranges.read_gtf(<PATH TO GTF>)
# OR
gr = genomicranges.read_ucsc(genome="hg19")

print(gr)
## output
## GenomicRanges with 1760959 intervals & 10 metadata columns.
## ... truncating the console print ...

from `IRanges` (Preferred way)

If you have all relevant information to create a GenomicRanges object

from genomicranges import GenomicRanges
from iranges import IRanges
from biocframe import BiocFrame
from random import random

gr = GenomicRanges(
    seqnames=[
        "chr1",
        "chr2",
        "chr3",
        "chr2",
        "chr3",
    ],
    ranges=IRanges(start=[x for x in range(101, 106)], width=[11, 21, 25, 30, 5]),
    strand=["*", "-", "*", "+", "-"],
    mcols=BiocFrame(
        {
            "score": range(0, 5),
            "GC": [random() for _ in range(5)],
        }
    ),
)

print(gr)

## output
GenomicRanges with 5 ranges and 5 metadata columns
    seqnames    ranges           strand     score                  GC
       <str> <IRanges> <ndarray[int64]>   <range>              <list>
[0]     chr1 101 - 112                * |       0  0.2593301003406461
[1]     chr2 102 - 123                - |       1  0.7207993213776644
[2]     chr3 103 - 128                * |       2 0.23391468067222065
[3]     chr2 104 - 134                + |       3  0.7671026589720187
[4]     chr3 105 - 110                - |       4 0.03355777784472458
------
seqinfo(3 sequences): chr1 chr2 chr3

Pandas DataFrame

A common representation in Python is a pandas DataFrame for all tabular datasets. DataFrame must contain columns "seqnames", "starts", and "ends" to represent genomic intervals. Here's an example:

import genomicranges import GenomicRanges
import pandas as pd

df = pd.DataFrame(
    {
        "seqnames": ["chr1", "chr2", "chr1", "chr3", "chr2"],
        "starts": [101, 102, 103, 104, 109],
        "ends": [112, 103, 128, 134, 111],
        "strand": ["*", "-", "*", "+", "-"],
        "score": range(0, 5),
        "GC": [random() for _ in range(5)],
    }
)

gr = GenomicRanges.from_pandas(df)
print(gr)

## output
GenomicRanges with 5 ranges and 5 metadata columns
  seqnames    ranges           strand    score                  GC
     <str> <IRanges> <ndarray[int64]>   <list>              <list>
0     chr1 101 - 112                * |      0  0.4862658925128007
1     chr2 102 - 103                - |      1 0.27948386889389953
2     chr1 103 - 128                * |      2  0.5162697718607901
3     chr3 104 - 134                + |      3  0.5979843806415466
4     chr2 109 - 111                - |      4 0.04740781186083798
------
seqinfo(3 sequences): chr1 chr2 chr3

Interval Operations

GenomicRanges supports most interval based operations.

subject = genomicranges.from_ucsc(genome="hg38")

query = genomicranges.from_pandas(
    pd.DataFrame(
        {
            "seqnames": ["chr1", "chr2", "chr3"],
            "starts": [100, 115, 119],
            "ends": [103, 116, 120],
        }
    )
)

hits = subject.nearest(query, ignore_strand=True)
print(hits)

## output
[[0, 1], [1677082, 1677083, 1677084], [1003411, 1003412]]

`GenomicRangesList`

Just as it sounds, a GenomicRangesList is a named-list like object. If you are wondering why you need this class, a GenomicRanges object lets us specify multiple genomic elements, usually where the genes start and end. Genes are themselves made of many sub-regions, e.g. exons. GenomicRangesList allows us to represent this nested structure.

Currently, this class is limited in functionality.

To construct a GenomicRangesList

gr1 = GenomicRanges(
    seqnames=["chr1", "chr2", "chr1", "chr3"],
    ranges=IRanges([1, 3, 2, 4], [10, 30, 50, 60]),
    strand=["-", "+", "*", "+"],
    mcols=BiocFrame({"score": [1, 2, 3, 4]}),
)

gr2 = GenomicRanges(
    seqnames=["chr2", "chr4", "chr5"],
    ranges=IRanges([3, 6, 4], [30, 50, 60]),
    strand=["-", "+", "*"],
    mcols=BiocFrame({"score": [2, 3, 4]}),
)
grl = GenomicRangesList(ranges=[gr1, gr2], names=["gene1", "gene2"])
print(grl)

## output
GenomicRangesList with 2 ranges and 2 metadata columns

Name: gene1
GenomicRanges with 4 ranges and 4 metadata columns
    seqnames    ranges           strand    score
       <str> <IRanges> <ndarray[int64]>   <list>
[0]     chr1    1 - 11                - |      1
[1]     chr2    3 - 33                + |      2
[2]     chr1    2 - 52                * |      3
[3]     chr3    4 - 64                + |      4
------
seqinfo(3 sequences): chr1 chr2 chr3

Name: gene2
GenomicRanges with 3 ranges and 3 metadata columns
    seqnames    ranges           strand    score
       <str> <IRanges> <ndarray[int64]>   <list>
[0]     chr2    3 - 33                - |      2
[1]     chr4    6 - 56                + |      3
[2]     chr5    4 - 64                * |      4
------
seqinfo(3 sequences): chr2 chr4 chr5

Further information

Note

This project has been set up using PyScaffold 4.1.1. For details and usage information on PyScaffold see https://pyscaffold.org/.

Release files for genomicranges 0.4.4

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Table of built distributions (wheels) for genomicranges 0.4.4
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