Plant_Annotation_TEs | Plant Genome Annotation - Transposable Elements | Data Labeling library

 by   amvarani Perl Version: v102 License: No License

kandi X-RAY | Plant_Annotation_TEs Summary

kandi X-RAY | Plant_Annotation_TEs Summary

Plant_Annotation_TEs is a Perl library typically used in Artificial Intelligence, Data Labeling applications. Plant_Annotation_TEs has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Transposable elements (TEs) are prominent features of a plant genome. During a plant genome annotation project, the TEs must be first identified before the structural gene annotation. After a proper TE annotation, all TE-derived regions in the genome must be masked (preferably soft-masked: repeats in lowercase rather than "N" or "X"). EDTA is one of the most powerful and complete TE annotation pipelines. However, EDTA has low power to annotate SINEs and LINEs. Using structural-based methods, the pipeline described here will create a non-redundant SINEs/LINEs library of your species' genome. These libraries can be further supplied to our modified version EDTA of the pipeline (--sine and --line flags). Moreover, it is known that the EDTA pipeline often generates many false positives TE predictions (mainly represented by TIRs elements).To avoid false positives, we developed an adaptation on the EDTA pipeline that tries to lower the false positive prediction of TIR elements. This adapted EDTA version also annotates non-autonomous LTR elements (e.g., LARD, TRIM, TR-GAG, and BARE-2). It comprehensively annotates SINE, LTR, and TIRs elements at their respective lineages. Furthermore, helitron elements are divided into autonomous (containing HEL domain) and non-autonomous (not containing HEL domain). The input is a fasta file containing the plant genome in chromosome-scale (preferably). The final result will be an augmented TE annotation (containing the outputs commonly generated by the EDTA pipeline), an adequately masked genome for structural gene annotation, and a complete TE report showing TE lineages abundances. Since this pipeline can retrieve complete CRM elements, it is possible to figure out the potential centromeric regions using other approaches with the trf tool. Important Notice 1: This pipeline was tested only on Ubuntu 20.20 and was made for Plant Genomes. Important Notice 2: This pipeline could be better and is under development for improvements.
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              Plant_Annotation_TEs has a low active ecosystem.
              It has 4 star(s) with 0 fork(s). There are 2 watchers for this library.
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              It had no major release in the last 12 months.
              Plant_Annotation_TEs has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of Plant_Annotation_TEs is v102

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              Plant_Annotation_TEs has no bugs reported.

            kandi-Security Security

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

            kandi-License License

              Plant_Annotation_TEs does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
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              Without a license, all rights are reserved, and you cannot use the library in your applications.

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              Plant_Annotation_TEs releases are available to install and integrate.
              Installation instructions, examples and code snippets are available.

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            Plant_Annotation_TEs Key Features

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            Plant_Annotation_TEs Examples and Code Snippets

            No Code Snippets are available at this moment for Plant_Annotation_TEs.

            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 Plant_Annotation_TEs

            The instalation is divided in four main steps.
            Download the Miniconda installer for Linux: https://docs.conda.io/en/latest/miniconda.html#linux-installers

            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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            https://github.com/amvarani/Plant_Annotation_TEs.git

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            gh repo clone amvarani/Plant_Annotation_TEs

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            git@github.com:amvarani/Plant_Annotation_TEs.git

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