rnalysis

Analyze your RNA sequencing data without writing a single line of code

https://github.com/guyteichman/rnalysis

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Analyze your RNA sequencing data without writing a single line of code

README.rst

.. image:: https://raw.githubusercontent.com/GuyTeichman/RNAlysis/master/docs/source/logo.png
    :target: https://guyteichman.github.io/RNAlysis
    :width: 250
    :align: center
    :alt: logo


`Documentation `_ |
`Source code `_ |
`Bug reports `_ |
|pipimage| | |versionssupported| |
|githubactions| | |coveralls| | |downloads|

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 What is *RNAlysis*?
----------------------

*RNAlysis* is a powerful, user-friendly software that allows you to analyze your RNA sequencing data without writing a single line of code.
This Python-based tool offers a complete solution for your RNA-seq analysis needs, from raw data processing to advanced statistical analyses and beautiful visualizations, all through an intuitive graphical interface.

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 See *RNAlysis* in Action
---------------------------

|quicksearch|

*Instantly access gene information from various biological databases with a simple right-click.*

|setops|

*Perform advanced set operations to extract and analyze specific subsets of your data.*

|autoreport|

*Easily generate comprehensive and intuitive analysis reports to promote reproducibility. Track the entire analysis path with just a click!*


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 Key Features
----------------

- **Code-Free Analysis**: Perform complex analyses with just a few clicks.
- **Comprehensive Analysis Pipeline**: From data import to enrichment analysis, all in one place.
- **Interactive Visualizations**: Explore your data with dynamic, publication-ready graphs.
- **Customizable Workflows**: Build and share analysis pipelines tailored to your research questions.
- **Integration with Popular Tools**: Seamless compatibility with DESeq2, kallisto, bowtie2, and more.
- **Rapid Gene Information Lookup**: Instantly access gene information from various biological databases.
- **Advanced Set Operations**: Easily extract and analyze specific subsets of your data.
- **Reproducible Research**: Generate comprehensive, interactive analysis reports with a single click.

To get an overview of what *RNAlysis* can do, read the `tutorial `_ and the `user guide `_.

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 How do I install it?
------------------------
You can either install *RNAlysis* as a stand-alone app, or via PyPI.
To learn how to install *RNAlysis*, visit the `Installation page `_.

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 How do I use it?
---------------------
If you installed *RNAlysis* as a stand-alone app, simply open the app ("RNAlysis.exe" on Windows, "RNAlysis.dmg" on MacOS) and wait for it to load (it may take a minute or two, so be patient!).

If you installed *RNAlysis* from PyPi, you can launch *RNAlysis* by typing the following command::

    rnalysis-gui

Or through a python console::

    >>> from rnalysis import gui
    >>> gui.run_gui()

In addition, you can write Python code that uses *RNAlysis* functions as described in the `programmatic interface user guide `_.

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Dependencies
------------
All of *RNAlysis*'s dependencies can be installed automatically via PyPI.

* `numpy `_
* `polars `_
* `pandas `_
* `scipy `_
* `matplotlib `_
* `numba `_
* `requests `_
* `scikit-learn `_
* `kmedoids `_
* `hdbscan `_
* `seaborn `_
* `statsmodels `_
* `joblib `_
* `tqdm `_
* `appdirs `_
* `grid_strategy `_
* `pyyaml `_
* `UpSetPlot `_
* `matplotlib-venn `_
* `xlmhglite `_
* `pairwisedist `_
* `typing_extensions `_
* `PyQt6 `_
* `qdarkstyle `_
* `defusedxml `_
* `cutadapt `_
* `aiohttp `_
* `aiodns `_
* `aiolimiter `_
* `Brotli `_
* `networkx `_
* `pyvis `_
* `tenacity `_

----

Credits
-------

How do I cite *RNAlysis*?
**************************
If you use *RNAlysis* in your research, please cite::

    Teichman, G., Cohen, D., Ganon, O., Dunsky, N., Shani, S., Gingold, H., and Rechavi, O. (2023).
    RNAlysis: analyze your RNA sequencing data without writing a single line of code. BMC Biology, 21, 74.
    https://doi.org/10.1186/s12915-023-01574-6

If you use the *CutAdapt* adapter trimming tool in your research, please cite::

    Martin, M. (2011). Cutadapt removes adapter sequences from high-throughput sequencing reads.
    EMBnet.journal, 17(1), pp. 10-12.
    https://doi.org/10.14806/ej.17.1.200

If you use the *kallisto* RNA sequencing quantification tool in your research, please cite::

    Bray, N., Pimentel, H., Melsted, P. et al.
    Near-optimal probabilistic RNA-seq quantification.
    Nat Biotechnol 34, 525527 (2016).
    https://doi.org/10.1038/nbt.3519

If you use the bowtie2 aligner in your research, please cite::

    Langmead, B., and Salzberg, S.L. (2012).
    Fast gapped-read alignment with Bowtie 2. Nat. Methods 2012 94 9, 357359.
    https://doi.org/10.1038/nmeth.1923

If you use the ShortStack aligner in your research, please cite::

    Axtell, MJ. (2013).
    ShortStack: Comprehensive annotation and quantification of small RNA genes. RNA 19:740-751.
    https://doi.org/10.1261/rna.035279.112


If you use the *DESeq2* differential expression tool in your research, please cite::

    Love MI, Huber W, Anders S (2014).
    Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.
    Genome Biology, 15, 550.
    https://doi.org/10.1186/s13059-014-0550-8

If you use the *Limma-Voom* differential expression pipeline in your research, please cite::

    Ritchie, M.E., Phipson, B., Wu, D., Hu, Y., Law, C.W., Shi, W., and Smyth, G.K. (2015).
    limma powers differential expression analyses for RNA-sequencing and microarray studies.
    Nucleic Acids Res. 43, e47e47.
    https://doi.org/10.1093/nar/gkv007

    Law, C.W., Chen, Y., Shi, W., and Smyth, G.K. (2014).
    Voom: Precision weights unlock linear model analysis tools for RNA-seq read counts.
    Genome Biol. 15, 117.
    https://doi.org/10.1186/gb-2014-15-2-r29


If you use the *HDBSCAN* clustering feature in your research, please cite::

     L. McInnes, J. Healy, S. Astels, hdbscan: Hierarchical density based clustering
    Journal of Open Source Software, The Open Journal, volume 2, number 11. 2017
    https://doi.org/10.1371/journal.pcbi.0030039

If you use the *XL-mHG* single-set enrichment test in your research, please cite::

    Eden, E., Lipson, D., Yogev, S., and Yakhini, Z. (2007).
     Discovering Motifs in Ranked Lists of DNA Sequences. PLOS Comput. Biol. 3, e39.
    https://doi.org/10.1371/journal.pcbi.0030039>doi.org/10.1371/journal.pcbi.0030039

    Wagner, F. (2017). The XL-mHG test for gene set enrichment. ArXiv.
    https://doi.org/10.48550/arXiv.1507.07905

If you use the *Ensembl* database in your research, please cite::

    Martin FJ, Amode MR, Aneja A, Austine-Orimoloye O, Azov AG, Barnes I, et al.
    Ensembl 2023. Nucleic Acids Res [Internet]. 2023 Jan 6;51(D1):D93341.
    doi.org/10.1093/nar/gkac958

If you use the *PANTHER* database in your research, please cite::

    Thomas PD, Ebert D, Muruganujan A, Mushayahama T, Albou L-P, Mi H.
    PANTHER: Making genome-scale phylogenetics accessible to all. Protein Sci [Internet]. 2022 Jan 1;31(1):822.
    doi.org/10.1002/pro.4218

If you use the *OrthoInspector* database in your research, please cite::

    Nevers Y, Kress A, Defosset A, Ripp R, Linard B, Thompson JD, et al.
    OrthoInspector 3.0: open portal for comparative genomics. Nucleic Acids Res [Internet]. 2019 Jan 8;47(D1):D4118.
    doi.org/10.1093/nar/gky1068

If you use the *PhylomeDB* database in your research, please cite::

    Fuentes D, Molina M, Chorostecki U, Capella-Gutirrez S, Marcet-Houben M, Gabaldn T.
    PhylomeDB V5: an expanding repository for genome-wide catalogues of annotated gene phylogenies. Nucleic Acids Res [Internet]. 2022 Jan 7;50(D1):D10628.
    doi.org/10.1093/nar/gkab966

If you use the *UniProt* gene ID mapping service in your research, please cite::

    The UniProt Consortium.
    UniProt: the Universal Protein Knowledgebase in 2023. Nucleic Acids Res [Internet]. 2023 Jan 6;51(D1):D52331.
    doi.org/10.1093/nar/gkac1052

Development Lead
******************

* Guy Teichman: guyteichman@gmail.com

Contributors
*************

* Dror Cohen
* Or Ganon
* Netta Dunsky
* Shachar Shani
* `Mintxoklet `_
* `Bipin Kumar `_
* Matthias Wilm
* `sandyl27 `_
* `clockgene `_
* `NeuroRookie `_

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This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage



.. |pipimage| image:: https://img.shields.io/pypi/v/rnalysis.svg
    :target: https://pypi.python.org/pypi/rnalysis
    :alt: PyPI version
.. |downloads| image:: https://pepy.tech/badge/rnalysis
    :target: https://pepy.tech/project/rnalysis
    :alt: Downloads
.. |versionssupported| image:: https://img.shields.io/pypi/pyversions/RNAlysis.svg
    :target: https://pypi.python.org/pypi/rnalysis
    :alt: Python versions supported

..  |githubactions| image:: https://github.com/guyteichman/RNAlysis/actions/workflows/build_ci.yml/badge.svg
    :target: https://github.com/GuyTeichman/RNAlysis/actions/workflows/build_ci.yml
    :alt: Build status

.. |coveralls| image:: https://coveralls.io/repos/github/GuyTeichman/RNAlysis/badge.svg?branch=master
    :target: https://coveralls.io/github/GuyTeichman/RNAlysis?branch=master
    :alt: Coverage
    :align: middle

..  |quicksearch| image:: https://github.com/GuyTeichman/RNAlysis/raw/master/rnalysis/gui/videos/quick_search.webp
    :alt: Rapid Gene Information Lookup
    :width: 600px


.. |setops| image:: https://github.com/GuyTeichman/RNAlysis/raw/master/rnalysis/gui/videos/set_operations.webp
    :alt: Set Operations
    :width: 600px


.. |autoreport| image:: https://github.com/GuyTeichman/RNAlysis/raw/master/rnalysis/gui/videos/report_overview.webp
    :alt: Interactive Analysis Report
    :width: 600px

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