Python package wrapping ENCODE epigenomic data for a number of reference cell lines.
Project description
Python package wrapping ENCODE epigenomic data for a number of 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 sometime get slightly different results, here’s three of them:
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
)
Finally, you can use a custom NaN threshold to drop windows that contain too many NaNs. For instance, if you want to drop the rows that have more than 60% of NaN you can use:
from epigenomic_dataset import build
build(
bed_path="path/to/my/bed/file.bed",
cell_lines=["HepG2", "H1"],
nan_threshold=0.6
)
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