SVclone | computational method for inferring the cancer cell fraction
kandi X-RAY | SVclone Summary
kandi X-RAY | SVclone Summary
SVclone is a Python library typically used in Healthcare, Pharma, Life Sciences applications. SVclone has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.
This package is used to cluster structural variants of similar cancer cell fraction (CCF). SVclone is divided into five components: annotate, count, filter, cluster and post-assign. The annotate step infers directionality of each breakpoint (if not supplied), recalibrates breakpoint position to the soft-clip boundary and subsequently classifies SVs using a rule-based approach. The count step counts the variant and non-variant reads from breakpoint locations. Both the annotate and count steps utilise BAM-level information. The filter step removes SVs based on a number of adjustable parameters and prepares the variants for clustering. SNVs can also be added at this step as well as CNV information, which is matched to SV and SNV loci. The post-assign step then allows SVs to be assigned to the derived model from SNV clustering. Optionally, SVs and SNVs can also be post-assigned to a joint SV + SNV model.
This package is used to cluster structural variants of similar cancer cell fraction (CCF). SVclone is divided into five components: annotate, count, filter, cluster and post-assign. The annotate step infers directionality of each breakpoint (if not supplied), recalibrates breakpoint position to the soft-clip boundary and subsequently classifies SVs using a rule-based approach. The count step counts the variant and non-variant reads from breakpoint locations. Both the annotate and count steps utilise BAM-level information. The filter step removes SVs based on a number of adjustable parameters and prepares the variants for clustering. SNVs can also be added at this step as well as CNV information, which is matched to SV and SNV loci. The post-assign step then allows SVs to be assigned to the derived model from SNV clustering. Optionally, SVs and SNVs can also be post-assigned to a joint SV + SNV model.
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Support
SVclone has a low active ecosystem.
It has 30 star(s) with 6 fork(s). There are 7 watchers for this library.
It had no major release in the last 12 months.
There are 1 open issues and 17 have been closed. On average issues are closed in 29 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of SVclone is 1.0.1
Quality
SVclone has 0 bugs and 0 code smells.
Security
SVclone has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
SVclone code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
SVclone is licensed under the BSD-3-Clause License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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SVclone releases are available to install and integrate.
Build file is available. You can build the component from source.
Installation instructions are not available. Examples and code snippets are available.
Top functions reviewed by kandi - BETA
kandi has reviewed SVclone and discovered the below as its top functions. This is intended to give you an instant insight into SVclone implemented functionality, and help decide if they suit your requirements.
- Run Picard
- Load csv file
- Load consensus consensus consensus
- Load SNVs from vcf file
- Run clustering step
- Format SNPs into a single dataframe
- Performs cluster clustering
- Extract SNV values from a dataframe
- Process sVs
- Calculate location counts
- Extract information from sv file
- Calculate read counts for SV reads
- Preprocess SVs
- Return the classification of an event
- Detects the coverage of the SV
- Classify a list of SVS
- Return a numpy array that matches two SVs
- Check if two svs are the same
- Writes the result to html
- Wrap a color string
Get all kandi verified functions for this library.
SVclone Key Features
No Key Features are available at this moment for SVclone.
SVclone Examples and Code Snippets
No Code Snippets are available at this moment for SVclone.
Community Discussions
No Community Discussions are available at this moment for SVclone.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install SVclone
You can download it from GitHub.
You can use SVclone like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use SVclone like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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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