Skip to main content

Python package wrapping ENCODE epigenomic data for a number of reference cell lines.

Project description

Travis CI build SonarCloud Quality SonarCloud Maintainability Codacy Maintainability Maintainability Pypi project Pypi total project downloads

Python package wrapping ENCODE epigenomic data for several reference cell lines.

How do I install this package?

As usual, just download it using pip:

pip install epigenomic_dataset

Tests Coverage

Since some software handling coverages sometimes get slightly different results, here’s three of them:

Coveralls Coverage SonarCloud Coverage Code Climate Coverate

TODO: THE FOLLOWING SECTION WILL NEED RESTRUCTURING IN A LITTLE BIT!

Preprocessed data for cis-regulatory regions

We have already downloaded and obtained the max window value for each promoter and enhancer region for the cell lines A549, GM12878, H1, HEK293, HepG2, K562 and MCF7 in the dataset Fantom and cell lines A549, GM12878, H1, HepG2 and K562 for the Roadmap dataset taking in consideration all the target features listed in the complete table of epigenomes.

The thresholds used for classifying the activations of enhancers and promoters in Fantom are the default explained in the sister pipeline CRR labels which handles the download and preprocessing of the data from Fantom and Roadmap.

Dataset

Assembly

Window Size

Region

Cell line

Download URL

fantom

hg38

256

promoters

GM12878

Download

fantom

hg38

256

promoters

A549

Download

fantom

hg38

256

promoters

HEK293

Download

fantom

hg38

256

promoters

HepG2

Download

fantom

hg38

256

promoters

K562

Download

fantom

hg38

256

promoters

H1

Download

fantom

hg38

256

promoters

MCF-7

Download

fantom

hg38

256

enhancers

GM12878

Download

fantom

hg38

256

enhancers

A549

Download

fantom

hg38

256

enhancers

HEK293

Download

fantom

hg38

256

enhancers

HepG2

Download

fantom

hg38

256

enhancers

K562

Download

fantom

hg38

256

enhancers

H1

Download

fantom

hg38

256

enhancers

MCF-7

Download

fantom

hg38

128

promoters

GM12878

Download

fantom

hg38

128

promoters

A549

Download

fantom

hg38

128

promoters

HEK293

Download

fantom

hg38

128

promoters

HepG2

Download

fantom

hg38

128

promoters

K562

Download

fantom

hg38

128

promoters

H1

Download

fantom

hg38

128

promoters

MCF-7

Download

fantom

hg38

128

enhancers

GM12878

Download

fantom

hg38

128

enhancers

A549

Download

fantom

hg38

128

enhancers

HEK293

Download

fantom

hg38

128

enhancers

HepG2

Download

fantom

hg38

128

enhancers

K562

Download

fantom

hg38

128

enhancers

H1

Download

fantom

hg38

128

enhancers

MCF-7

Download

fantom

hg38

64

promoters

GM12878

Download

fantom

hg38

64

promoters

A549

Download

fantom

hg38

64

promoters

HEK293

Download

fantom

hg38

64

promoters

HepG2

Download

fantom

hg38

64

promoters

K562

Download

fantom

hg38

64

promoters

H1

Download

fantom

hg38

64

promoters

MCF-7

Download

fantom

hg38

64

enhancers

GM12878

Download

fantom

hg38

64

enhancers

A549

Download

fantom

hg38

64

enhancers

HEK293

Download

fantom

hg38

64

enhancers

HepG2

Download

fantom

hg38

64

enhancers

K562

Download

fantom

hg38

64

enhancers

H1

Download

fantom

hg38

64

enhancers

MCF-7

Download

fantom

hg38

1024

promoters

GM12878

Download

fantom

hg38

1024

promoters

A549

Download

fantom

hg38

1024

promoters

HEK293

Download

fantom

hg38

1024

promoters

HepG2

Download

fantom

hg38

1024

promoters

K562

Download

fantom

hg38

1024

promoters

H1

Download

fantom

hg38

1024

promoters

MCF-7

Download

fantom

hg38

1024

enhancers

GM12878

Download

fantom

hg38

1024

enhancers

A549

Download

fantom

hg38

1024

enhancers

HEK293

Download

fantom

hg38

1024

enhancers

HepG2

Download

fantom

hg38

1024

enhancers

K562

Download

fantom

hg38

1024

enhancers

H1

Download

fantom

hg38

1024

enhancers

MCF-7

Download

fantom

hg38

512

promoters

GM12878

Download

fantom

hg38

512

promoters

A549

Download

fantom

hg38

512

promoters

HEK293

Download

fantom

hg38

512

promoters

HepG2

Download

fantom

hg38

512

promoters

K562

Download

fantom

hg38

512

promoters

H1

Download

fantom

hg38

512

promoters

MCF-7

Download

fantom

hg38

512

enhancers

GM12878

Download

fantom

hg38

512

enhancers

A549

Download

fantom

hg38

512

enhancers

HEK293

Download

fantom

hg38

512

enhancers

HepG2

Download

fantom

hg38

512

enhancers

K562

Download

fantom

hg38

512

enhancers

H1

Download

fantom

hg38

512

enhancers

MCF-7

Download

Here are the labels for all the considered cell lines.

Dataset

Promoters

Enhancers

Fantom

200

1000

200

1000

Roadmap

200

1000

200

1000

TODO: align promoters and enhancers in a reference labels dataset.

The complete pipeline used to retrieve the CRR epigenomic data is available here.

Automatic retrieval of preprocessed data

You can automatically retrieve the data as follows:

from epigenomic_dataset import load_epigenomes

X, y = load_epigenomes(
    cell_line = "K562",
    dataset = "fantom",
    region = "promoters",
    window_size = 256,
    root = "datasets" # Path where to download data
)

Pipeline for epigenomic data

The considered raw data are from this query from the ENCODE project

You can find the complete table of the available epigenomes here. These datasets were selected to have (at time of the writing, 07/02/2020) the least possible amount of known problems, such as low read resolution.

You can run the pipeline as follows: suppose you want to extract the epigenomic features for the cell lines HepG2 and H1:

from epigenomic_dataset import build

build(
    bed_path="path/to/my/bed/file.bed",
    cell_lines=["HepG2", "H1"]
)

If you want to specify where to store the files use:

from epigenomic_dataset import build

build(
    bed_path="path/to/my/bed/file.bed",
    cell_lines=["HepG2", "H1"],
    path="path/to/my/target"
)

By default, the downloaded bigWig files are not deleted. You can choose to delete the files as follows:

from epigenomic_dataset import build

build(
    bed_path="path/to/my/bed/file.bed",
    cell_lines=["HepG2", "H1"],
    path="path/to/my/target",
    clear_download=True
)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

epigenomic_dataset-1.2.14.tar.gz (16.6 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page