NanoSeq | Time Series sequence decoding using HMM and RNN - A

by sudiptodip15 Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | NanoSeq Summary

NanoSeq is a Python library. NanoSeq has no bugs, it has no vulnerabilities and it has low support. However NanoSeq build file is not available. You can download it from GitHub.

Time Series sequence decoding using HMM and RNN - A comparison

Support

Quality

Security

License

Reuse

Support

NanoSeq has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

NanoSeq has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of NanoSeq is current.

Quality

NanoSeq has 0 bugs and 0 code smells.

Security

NanoSeq has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

NanoSeq code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

NanoSeq does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

NanoSeq releases are not available. You will need to build from source code and install.

NanoSeq 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.

Top functions reviewed by kandi - BETA

kandi has reviewed NanoSeq and discovered the below as its top functions. This is intended to give you an instant insight into NanoSeq implemented functionality, and help decide if they suit your requirements.

Gets tensorflow tensorflow tensorflow tensors .
Decode the current sequence into a probability matrix
Compute transmat from a list of files .
Compute the observed obsmat file .
Compute the transmat matrix of the transition matrix .
Run Viterbi on a transition matrix .
Run Viterbi using Viterbi .
Runs the predictive accuracy .
Compute observation matrix .
Write sequence to fasta file

Get all kandi verified functions for this library.

NanoSeq Key Features

No Key Features are available at this moment for NanoSeq.

NanoSeq Examples and Code Snippets

No Code Snippets are available at this moment for NanoSeq.

Community Discussions

No Community Discussions are available at this moment for NanoSeq.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install NanoSeq

Please note that number of train, test and validate datasets need to changed in the code of RNN. They currently have some default values.
Git clone and run 'tar -xzf NanoData_5mer.tar.gz` to extract the Data folder.
python mainHMM.py to obtain the decoded sequence fasta files of Test set after learning parameters of HMM viz. Transition and Observation matrix.
python mainNaive.py to learn the Observation matrix and fit a Gaussian likelihood function without incorporating time transitions.
python mainNanoRNN.py to obtain the performance on test data of RNN.

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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