Unit tests

SummarizedExperiment

Container to represent genomic experiments, follows Bioconductor's SummarizedExperiment.

Install

Package is published to PyPI,

pip install summarizedexperiment

Usage

Currently supports SummarizedExperiment & RangedSummarizedExperiment classes

First create necessary sample data

from random import random
import pandas as pd
import numpy as np
from biocframe import BiocFrame

nrows = 200
ncols = 6
counts = np.random.rand(nrows, ncols)
row_data = BiocFrame(
    {
        "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,
    }
)

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

To create a SummarizedExperiment,

from summarizedexperiment import SummarizedExperiment

tse = SummarizedExperiment(
    assays={"counts": counts}, row_data=row_data, column_data=col_data,
    metadata={"seq_platform": "Illumina NovaSeq 6000"},
)

## output
class: SummarizedExperiment
dimensions: (200, 6)
assays(1): ['counts']
row_data columns(6): ['seqnames', 'starts', 'ends', 'strand', 'score', 'GC']
row_names(0):
column_data columns(1): ['treatment']
column_names(0):
metadata(1): seq_platform

To create a RangedSummarizedExperiment

from summarizedexperiment import RangedSummarizedExperiment
from genomicranges import GenomicRanges

trse = RangedSummarizedExperiment(
    assays={"counts": counts}, row_data=row_data,
    row_ranges=GenomicRanges.from_pandas(row_data.to_pandas()), column_data=col_data
)

## output
class: RangedSummarizedExperiment
dimensions: (200, 6)
assays(1): ['counts']
row_data columns(6): ['seqnames', 'starts', 'ends', 'strand', 'score', 'GC']
row_names(0):
column_data columns(1): ['treatment']
column_names(0):
metadata(0):

For more examples, checkout the documentation.

Note

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

Release files for summarizedexperiment 0.4.4

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for summarizedexperiment 0.4.4
File	Size	Uploaded
summarizedexperiment-0.4.4.tar.gz	1.0 MB	May 16, 2024	Details

Built distribution (wheel)

Table of built distributions (wheels) for summarizedexperiment 0.4.4
File	Interpreter	ABI	Platform	Reset
SummarizedExperiment-0.4.4-py3-none-any.whl 21.5 kB May 16, 2024	Python 3	none	any	Details

Total release size: 1.0 MB

Release files / summarizedexperiment-0.4.4.tar.gz

Download URL	summarizedexperiment-0.4.4.tar.gz
Size	1.0 MB
Tags	Source
SHA-256 checksum How to use checksums	`fac54102e21c48a282ffd7c3fae23f968f5dcc640cc62d886f6d40e62838d915`
BLAKE2b-256 checksum How to use checksums	`127ee15d81a763fc08c8a190bb9952d72111e43ada2c9962277fec4a89b4d425`
Upload date	May 16, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/5.1.0 CPython/3.9.19`

Release files / SummarizedExperiment-0.4.4-py3-none-any.whl

Download URL	SummarizedExperiment-0.4.4-py3-none-any.whl
Size	21.5 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`97933291194a0deb2a3bf7881526c0f2385eca5657423019a6b70dfc105bd5ed`
BLAKE2b-256 checksum How to use checksums	`0ccc284540ddb58156e2b09d60a98da1fa68c997d8e0bb213da0e9af1621a063`
Upload date	May 16, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/5.1.0 CPython/3.9.19`