SpliceAI | A deep learning-based tool to identify splice variants | Genomics library

by Illumina Python Version: v1.3.1 License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | SpliceAI Summary

SpliceAI is a Python library typically used in Artificial Intelligence, Genomics applications. SpliceAI has no bugs, it has no vulnerabilities, it has build file available and it has low support. However SpliceAI has a Non-SPDX License. You can download it from GitHub.

This package annotates genetic variants with their predicted effect on splicing, as described in Jaganathan et al, Cell 2019 in press. Update: The annotations for all possible substitutions, 1 base insertions, and 1-4 base deletions within genes are available here for download. These annotations are free for academic and not-for-profit use; other use requires a commercial license from Illumina, Inc.

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SpliceAI has a low active ecosystem.

It has 299 star(s) with 130 fork(s). There are 16 watchers for this library.

It had no major release in the last 6 months.

There are 6 open issues and 103 have been closed. On average issues are closed in 41 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of SpliceAI is v1.3.1

Quality

SpliceAI has 0 bugs and 0 code smells.

Security

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

SpliceAI code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

SpliceAI has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

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

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

SpliceAI saves you 113 person hours of effort in developing the same functionality from scratch.

It has 285 lines of code, 12 functions and 6 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Get delta scores for a given alignment
Converts a sequence into one - hot encode
Return the name and strand of a chromosome
Normalise chromosomes
Calculate the position annotation for a given position
Argument parser

Get all kandi verified functions for this library.

SpliceAI Key Features

No Key Features are available at this moment for SpliceAI.

SpliceAI Examples and Code Snippets

No Code Snippets are available at this moment for SpliceAI.

Community Discussions

Trending Discussions on SpliceAI

google cloud function needs large (3Gb) reference data file to compute result

QUESTION

google cloud function needs large (3Gb) reference data file to compute result

Asked 2020-Jun-21 at 03:46

I want to write a google cloud run function that runs a bioinformatics tool. This tool takes a large 3Gb reference data file as a read-only input (https://github.com/Illumina/SpliceAI#usage) + a small 2nd file which varies based on user input.
Should I try to build the reference data file into my docker image, or is there a better way?

...

ANSWER

Answered 2020-Jun-21 at 03:46

Using Cloud Run your only option is to bake the file into your container. If you use external storage for it and then read it into Cloud Run you will go way over the memory quota which is 2GB. Since Cloud Run also uses system memory for any files you write when it runs, you literally can't read the file into the container at runtime. Interestingly Cloud Run does not count files baked into the container against this limit, which is discussed here: Does Google Cloud Run memory limit apply to the container size?

I have no idea what will happen with a 3GB container, but it shouldn't be too hard to test. Of course you will have issues with the memory limit, if you need to read the entire data file to memory.

If there are issues with it you should probably be looking at another service like App Engine Flexible which will allow you to use persistent disks and much higher memory sizes.

Source https://stackoverflow.com/questions/62494050

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

Vulnerabilities

No vulnerabilities reported

Install SpliceAI

The simplest way to install SpliceAI is through pip or conda:.

Support

SpliceAI only annotates variants within genes defined by the gene annotation file. Additionally, SpliceAI does not annotate variants if they are close to chromosome ends (5kb on either side), deletions of length greater than twice the input parameter -D, or inconsistent with the reference fasta file. The raw files also include splicing changes corresponding to strengthening annotated splice sites and weakening unannotated splice sites, which are typically much less pathogenic than weakening annotated splice sites and strengthening unannotated splice sites. The delta scores of such splicing changes are set to 0 in the masked files. We recommend using raw files for alternative splicing analysis and masked files for variant interpretation.

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