rp-bp | Bayesian approach to predict , at base-pair resolution

by dieterich-lab Python Version: 3.0.1 License: MIT

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kandi X-RAY | rp-bp Summary

rp-bp is a Python library. rp-bp has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However rp-bp build file is not available. You can install using 'pip install rp-bp' or download it from GitHub, PyPI.

An unsupervised Bayesian approach to predict translated open reading frames (ORFs) from ribosome profiles, using an automatic Bayesian Periodic fragment length and ribosome P-site offset Selection (BPPS).

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Quality

Security

License

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Support

rp-bp has a low active ecosystem.

It has 5 star(s) with 5 fork(s). There are 8 watchers for this library.

It had no major release in the last 12 months.

There are 4 open issues and 126 have been closed. On average issues are closed in 463 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of rp-bp is 3.0.1

Quality

rp-bp has no bugs reported.

Security

rp-bp has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

rp-bp is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

rp-bp releases are available to install and integrate.

Deployable package is available in PyPI.

rp-bp has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are available. Examples and code snippets are not available.

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rp-bp Key Features

No Key Features are available at this moment for rp-bp.

rp-bp Examples and Code Snippets

No Code Snippets are available at this moment for rp-bp.

Community Discussions

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Vulnerabilities

No vulnerabilities reported

Install rp-bp

This package is written in Python3. It has a number of external dependencies, mostly standard bioinformatics tools. Rp-Bp is not published on PyPI, but the installation is easily managed through pip3. The required privileges are determined by the installation location of pip3. In particular, if pip3 does not require sudo access, then none of the installation process requires sudo access; this is the case within a virtual environment, for example. For detailed instructions, including dependencies/prerequisites and step-by-step details of installing within a virtual environment and anaconda. refer to installation instructrions.