m6anet | Detection of m6A from direct RNA-Seq data
kandi X-RAY | m6anet Summary
kandi X-RAY | m6anet Summary
m6anet is a Python library. m6anet has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install m6anet' or download it from GitHub, PyPI.
m6anet is a python tool to detect m6a modifications from Nanopore Direct RNA Sequencing data.
m6anet is a python tool to detect m6a modifications from Nanopore Direct RNA Sequencing data.
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Quality
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Support
m6anet has a low active ecosystem.
It has 57 star(s) with 11 fork(s). There are 4 watchers for this library.
It had no major release in the last 12 months.
There are 7 open issues and 56 have been closed. On average issues are closed in 39 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of m6anet is 2.1.0
Quality
m6anet has 0 bugs and 0 code smells.
Security
m6anet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
m6anet code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
m6anet is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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m6anet releases are available to install and integrate.
Deployable package is available in PyPI.
Build file is available. You can build the component from source.
Installation instructions, examples and code snippets are available.
It has 1630 lines of code, 151 functions and 23 files.
It has medium code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed m6anet and discovered the below as its top functions. This is intended to give you an instant insight into m6anet implemented functionality, and help decide if they suit your requirements.
- Cross validation
- Build a data loader
- Build a Dataset object
- Build the loss function
- Preprocess a single transcript
- Combine multiple sequences
- Filter partitions by kers
- Split events into continuous positions
- Train and save the model
- Performs the parallel preprocessing of the event alignment
- Create an index for an event alignment
- Run inference
- Build the model
- Calculate mean standard deviation
- Argument parser
- Get command line arguments
- Create attention layer
- Perform the forward computation
- Creates a pandas dataframe from merged reads
- Compute the kmer for each group
- Create the nn layer
- Annotate kmer information
- Compute norm factors for k - merges
- Create a dictionary of normalized norm values
- Forward attention weights
- Compute norm factors from kmer information
- Create a dictionary mapping kmer to kmer
Get all kandi verified functions for this library.
m6anet Key Features
No Key Features are available at this moment for m6anet.
m6anet Examples and Code Snippets
No Code Snippets are available at this moment for m6anet.
Community Discussions
No Community Discussions are available at this moment for m6anet.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install m6anet
m6anet requires Python3 to run. To install our m6anet package and its dependencies, run.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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