SummarizedExperiment 0.1.2

Container to represent data from genomic experiments

SummarizedExperiment

Container to represent data from genomic experiments, follows Bioconductor's SummarizedExperiment. It uses efficient structures already available in the Pandas/numpy eco-system & adds a familiar interface.

Install

Package is published to PyPI

pip install summarizedexperiment

Usage

Currently supports both SummarizedExperiment & RangeSummarizedExperiment objects

First create necessary sample data

nrows = 200
ncols = 6
counts = np.random.rand(nrows, ncols)
df_gr = pd.DataFrame(
    {
        "seqnames": [
            "chr1",
            "chr2",
            "chr2",
            "chr2",
            "chr1",
            "chr1",
            "chr3",
            "chr3",
            "chr3",
            "chr3",
        ]
        * 20,
        "starts": range(100, 300),
        "ends": range(110, 310),
        "strand": ["-", "+", "+", "*", "*", "+", "+", "+", "-", "-"] * 20,
        "score": range(0, 200),
        "GC": [random() for _ in range(10)] * 20,
    }
)

gr = GenomicRanges.fromPandas(df_gr)

colData = pd.DataFrame(
    {
        "treatment": ["ChIP", "Input"] * 3,
    }
)

To create a SummarizedExperiment,

tse = SummarizedExperiment(
    assays={"counts": counts}, rowData=df_gr, colData=colData
)

To create a RangeSummarizedExperiment

trse = SummarizedExperiment(
    assays={"counts": counts}, rowRanges=gr, colData=colData
)

For more use cases including subset, checkout the documentation

Note

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