epigenomic-dataset 1.0.3

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

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:

Preprocessed data for cis-regulatory regions

We have already downloaded and obtained mean and max for each promoter and enhancer region for the cell lines A549, GM12878, H1, HEK293, HepG2, K562, MCF7, taking in consideration all the targets listed in the complete table of epigenomes.

The promoters and enhancers considered are taken from FANTOM, as can be downloaded by using the crr_labels pipeline.

The specific bed files and labels used can be found here for the promoters and here for the enhancers.

Cell line	Promoters epigenomes	Enhancers epigenomes	Features number
A549	Download	Download	54
GM12878	Download	Download	110
H1	Download	Download	43
HEK293	Download	Download	207
HepG2	Download	Download	209
K562	Download	Download	320
MCF7	Download	Download	101
All cell lines	Download	Download	1044

Pipeline

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
)