GenomicRanges 0.3.3

Container class to represent genomic locations and support genomic analysis.

GenomicRanges

Container class to represent genomic locations and support genomic analysis in Python similar to Bioconductor's GenomicRanges.

Install

Package is published to PyPI

pip install genomicranges

Usage

The package provide several ways to represent genomic annotations and intervals.

Initialize a GenomicRanges object

From UCSC or GTF file

Methods are available to easily access UCSC genomes or load a genome annotation from GTF

import genomicranges

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

Pandas DataFrame

A common representation in Python is a pandas DataFrame for all tabular datasets. One can convert this into GenomicRanges. Intervals are inclusive on both ends.

Note: DataFrame must contain columns seqnames, starts and ends to represent genomic coordinates.

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)

Interval Operations

Currently supports most commonly used 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)
print(hits)

Checkout the documentation for more usecases.

Note

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