Python package to generate on-hot encoded biological gaps to use for training and prediction.
Project description
Python package to generate on-hot encoded biological gaps to use for training and prediction.
How do I install this package?
As usual, just download it using pip:
pip install keras_biological_gaps_sequences
Tests Coverage
Since some software handling coverages sometimes get slightly different results, here’s three of them:
Available datasets
Currently, there is only a dataset of gaps available within the package: the mapping of known gaps from hg19 to hg38. In the future, we will be adding more mapping.
Usage example
To use the sequence you can do as follows:
biological_gap_sequence = BiologicalGapsSequence(
source="hg19",
target="hg38",
source_window_size=1000,
target_window_size=1000,
batch_size=32
)
model = build_my_denoiser()
model.fit_generator(
biological_gap_sequence,
steps_per_epoch=biological_gap_sequence.steps_per_epoch,
epochs=2,
shuffle=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
File details
Details for the file keras_biological_gaps_sequence-1.0.3.tar.gz
.
File metadata
- Download URL: keras_biological_gaps_sequence-1.0.3.tar.gz
- Upload date:
- Size: 4.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.4.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5a239981bc67a26398344327fdae7371bdca3078a8644728f4e1c5560bb50b43 |
|
MD5 | 5384028caaab367aa51c1a106bbae900 |
|
BLAKE2b-256 | b7d765e395c893d7400ba40b6374aaa0431fcc8ce07ec2198920da8cd8dcf6f5 |