Skip to main content

Python package to generate on-hot encoded biological gaps to use for training and prediction.

Project description

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

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:

Coveralls Coverage SonarCloud Coverage Code Climate Coverate

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(

model = build_my_denoiser()

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

keras_biological_gaps_sequence-1.0.3.tar.gz (4.7 kB view hashes)

Uploaded source

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page