SnpEffWrapper | Takes a VCF and applies annotations from a GFF using SnpEff | Data Labeling library

 by   sanger-pathogens Python Version: v0.2.5 License: GPL-3.0

kandi X-RAY | SnpEffWrapper Summary

kandi X-RAY | SnpEffWrapper Summary

SnpEffWrapper is a Python library typically used in Artificial Intelligence, Data Labeling applications. SnpEffWrapper has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

SnpEff is a tool that annotates and predicts the effects of variants on genes. SnpEffWrapper takes a VCF and, using SnpEff, infers annotations and variation effects from a GFF. If you use SnpEffWrapper, please consider citing SnpEff. This software is not endorsed in any respect by the original authors.
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            kandi-support Support

              SnpEffWrapper has a low active ecosystem.
              It has 4 star(s) with 3 fork(s). There are 14 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 3 open issues and 0 have been closed. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of SnpEffWrapper is v0.2.5

            kandi-Quality Quality

              SnpEffWrapper has 0 bugs and 0 code smells.

            kandi-Security Security

              SnpEffWrapper has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              SnpEffWrapper code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              SnpEffWrapper is licensed under the GPL-3.0 License. This license is Strong Copyleft.
              Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

            kandi-Reuse Reuse

              SnpEffWrapper releases are available to install and integrate.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              It has 603 lines of code, 31 functions and 5 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed SnpEffWrapper and discovered the below as its top functions. This is intended to give you an instant insight into SnpEffWrapper implemented functionality, and help decide if they suit your requirements.
            • Check that the VCF contigs are consistent with the coding table .
            • Get output files .
            • Ensure the arguments passed to the command line .
            • Check for common issues .
            • Annotate a VCF file with annotations .
            • Annotate VCF using snpeff .
            • Create a configuration file .
            • Get the contigs from a GFF file
            • Get the contigs from a VCF file .
            • Runs snpEff using snpEff .
            Get all kandi verified functions for this library.

            SnpEffWrapper Key Features

            No Key Features are available at this moment for SnpEffWrapper.

            SnpEffWrapper Examples and Code Snippets

            No Code Snippets are available at this moment for SnpEffWrapper.

            Community Discussions

            QUESTION

            How can I do this split process in Python?
            Asked 2021-Dec-30 at 14:06

            I'm trying to make a data labeling in a table, and I need to do it in such a way that, in each row, the index is repeated, however, that in each column there is another Enum class.

            What I've done so far is make this representation with the same enumerator class.

            A solution using the column separately as a list would also be possible. But what would be the best way to resolve this?

            ...

            ANSWER

            Answered 2021-Dec-30 at 13:57

            Instead of using Enum you can use a dict mapping. You can avoid loops if you flatten your dataframe:

            Source https://stackoverflow.com/questions/70532286

            QUESTION

            Replacing a character with a space and dividing the string into two words in R
            Asked 2020-Nov-18 at 07:32

            I have a dataframe that contains a column that includes strings separeted with semi-colons and it is followed by a space. But unfortunately in some of the strings there is a semi-colon that is not followed by a space.

            In this case, This is what i'd like to do: If there is a space after the semi-colon we do not need a change. However if there are letters before and after the semi-colon, we should change semi-colon with space

            i have this:

            ...

            ANSWER

            Answered 2020-Nov-16 at 07:24

            QUESTION

            Azure ML FileDataset registers, but cannot be accessed for Data Labeling project
            Asked 2020-Oct-28 at 20:31

            Objective: Generate a down-sampled FileDataset using random sampling from a larger FileDataset to be used in a Data Labeling project.

            Details: I have a large FileDataset containing millions of images. Each filename contains details about the 'section' it was taken from. A section may contain thousands of images. I want to randomly select a specific number of sections and all the images associated with those sections. Then register the sample as a new dataset.

            Please note that the code below is not a direct copy and paste as there are elements such as filepaths and variables that have been renamed for confidentiality reasons.

            ...

            ANSWER

            Answered 2020-Oct-27 at 22:39

            Is the data behind virtual network by any chance?

            Source https://stackoverflow.com/questions/64546521

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

            Vulnerabilities

            No vulnerabilities reported

            Install SnpEffWrapper

            SnpEffWrapper has the following dependencies:. Details for the installation are provided below. If you encounter an issue when installing SnpEffWrapper please contact your local system administrator. If you encounter a bug please log it here or email us at path-help@sanger.ac.uk. Install snpEff and Java 1.7 then.
            SnpEff (>= 4.1)
            Java (>= 1.7)
            Jinja2
            PyVCF
            PyYAML

            Support

            Please report any issues to the issues page or email path-help@sanger.ac.uk.
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