**circtools**
======================================================================
**a one-stop software solution for circular RNA research**
.. figure:: https://raw.githubusercontent.com/jakobilab/circtools/master/docs/img/circtools_200px.png
:alt: circtools
Introduction
-------------
Circular RNAs (circRNAs) originate through back-splicing events from linear primary transcripts, are resistant to exonucleases, typically not polyadenylated, and have been shown to be highly specific for cell type and developmental stage. Although few circular RNA molecules have been shown to exhibit miRNA sponge function, for the vast majority of circRNAs however, their function is yet to be determined.
The prediction of circular RNAs is a multi-stage bioinformatics process starting with raw sequencing data and usually ending with a list of potential circRNA candidates which, depending on tissue and condition may contain hundreds to thousands of potential circRNAs. While there already exist a number of tools for the prediction process (e.g. `DCC <https://github.com/dieterich-lab/DCC>`__ and `CircTest <https://github.com/dieterich-lab/CircTest>`__), publicly available downstream analysis tools are rare.
We developed **circtools**, a modular, Python3-based framework for circRNA-related tools that unifies several functionalities in single command line driven software. The command line follows the `circtools subcommand` standard that is employed in samtools or bedtools. Currently, circtools includes modules for detecting and reconstructing circRNAs,
a quick check of circRNA mapping results, RBP enrichment screenings, circRNA primer design, statistical testing, and an exon usage module.
Documentation
-------------
Click `here <https://docs.circ.tools/>`__ to access the complete documentation on Read the Docs.
Installation
------------
Via docker [NEW in 2.0]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The latest circtools docker version will be downloaded directly from GitHub. The container contains `all` dependencies required to run `circtools` except STAR and Bowtie.
.. code-block:: console
docker pull ghcr.io/jakobilab/circtools/circtools:latest
An bash alias to call circtools "natively" and skip the unwieldy full docker command is recommended:
.. code-block:: console
alias circtools='docker run --rm -v "`pwd`":/circtools/ ghcr.io/jakobilab/circtools/circtools'
This line can be added to the `.bashrc` or `.profile` file to be automatically loaded after login.
Via pip
~~~~~~~~~~~~~~~
The ``circtools`` package is written in Python 3 (supporting Python 3.8 - 3.12). It requires only a small number of external dependencies, namely standard bioinformatics tools:
- `bedtools (>= 2.27.1) <https://bedtools.readthedocs.io/en/latest/content/installation.html>`__
[RBP enrichment module, installed automatically]
- `R (>= 4.0) <https://www.digitalocean.com/community/tutorials/how-to-install-r-on-ubuntu-22-04>`__
[Data visualization and data processing]
Installation is managed through ``pip3 install circtools`` or ``python3 setup.py
install`` when installed from the cloned GitHub repository. No sudo access is
required if the installation is executed in an virtual environment which will install the
package in a user-writeable folder. The binaries should be installed
to ``/home/$user/.local/bin/`` in case of Debian-based systems.
``circtools`` was developed and tested on Debian Bookworm, but should also
run with any other distribution.
The installation can be performed directly from PyPi:
.. code-block:: console
# create virtual environment
python3 -m venv circtools
# activate virtual environment
source circtools/bin/activate
# install circtools
pip install numpy # required for HTSeq, dependency of circtools
pip install circtools
# install R packages for circtools
circtools_install_R_dependencies
Via git (development version)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Additionally, this repository offers the latest development version:
.. code-block:: console
pip install numpy # required for HTSeq, a dependency of circtools
pip install git+https://github.com/jakobilab/circtools.git
The primer-design module as well as the exon analysis and circRNA testing module
require a working installation of `R <https://cran.r-project.org/>`__ with
`BioConductor <https://www.bioconductor.org/install/>`__. All R packages
required can be automatically installed during the setup. Please see the
`"Installing circtools" <http://docs.circ.tools/en/latest/Installation.html>`__
chapter of the main circtools documentation for more detailed installation instructions.
Modules
-------
Circtools currently offers the following modules:
nanopore `(detailed documentation) <https://docs.circ.tools/en/latest/Nanopore.html>`__ [NEW in 2.0]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Recent advances in long-read sequencing technologies have enabled the generation of
full-length circRNA sequences. The module is based on
`long_read_circRNA <https://github.com/omiics-dk/long_read_circRNA>`__ and designed to specifically process the
unique characteristics of Oxford Nanopore data, i.e. the handling of sequencing
reads > 5kb, and provides accurate and efficient detection of circRNAs.
padlock `(detailed documentation) <https://docs.circ.tools/en/latest/Conservation.html>`__ [NEW in 2.0]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Spatial transcriptomics emerged as a powerful technique to map the localization of
single molecules to the level of individual cells and even offer subcellular resolution.
Although most of the high-throughput methods were designed with linear polyadenylated
RNAs in mind, some methods could target circRNAs as well. This module is
specifically tailored to the Xenium platform as it offers subcellular resolution
and an option for custom panel design. The module requires three inputs: 1)
circRNA coordinates detected using \textit{circtools}' detect step, 2)
a genome FASTA file, and 3) a transcriptome GTF file.
conservation `(detailed documentation) <https://docs.circ.tools/en/latest/Conservation.html>`__ [NEW in 2.0]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Evolutionary conservation analysis oftentimes uncovers the potential
functional relevance of circRNAs by comparing their sequence and genomic
position across different organisms. We developed the conservation module
to enable users to perform circRNA conservation analysis in five widely
studied animal model species: mouse, human, rat, pig, and dog. The framework
of the conservation module was developed with the flexibility to incorporate
more species in the analysis by simply adding the species to the input config file.
detect/metatool `(detailed documentation) <https://docs.circ.tools/en/latest/Detect.html>`__ [Updated in 2.0]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The ``detect`` command is an interface to
`DCC <https://github.com/dieterich-lab/DCC>`__, developed at the
Dieterich Lab. The module allows to detect circRNAs from RNA sequencing
data. The module is the foundation of all other steps for the circtools
work flow. All parameters supplied to circtools will be directly passed
to DCC. The detect module also performs the new metatool functionality
added with circtools 2.0 which enables the addition of circRNA counts
generated with `ciriquant` to further improve recall rates.
quickcheck `(detailed documentation) <https://docs.circ.tools/en/latest/Quickcheck.html>`__
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The quickcheck module of circtools is an easy way to check the results
of a DCC run for problems and to quickly assess the number of circRNAs
in a given experiment. The module needs the mapping log files produced
by STAR as well as the directory with the DCC results. The module than
generates a series of figures in PDF format to assess the results.
reconstruct `(detailed documentation) <https://docs.circ.tools/en/latest/Reconstruct.html>`__
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The ``reconstruct`` command is an interface to
`FUCHS <https://github.com/dieterich-lab/FUCHS>`__. FUCHS is employing
DCC-generated data to reconstruct circRNA structures. All parameters
supplied to circtools will be directly passed to FUCHS.
circtest `(detailed documentation) <https://docs.circ.tools/en/latest/Circtest.html>`__
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The ``circtest`` command is an interface to
`CircTest <https://github.com/dieterich-lab/CircTest>`__. The module a a
very convenient way to employ statistical testing to circRNA candidates
generated with DCC without having to write an R script for each new
experiment. For detailed information on the implementation itself take a
look at the `CircTest
documentation <https://github.com/dieterich-lab/CircTest>`__. In
essence, the module allows dynamic grouping of the columns (samples) in
the DCC data.
exon `(detailed documentation) <https://docs.circ.tools/en/latest/Exon.html>`__
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The exon module of circtools employs the `ballgown R
package <https://www.bioconductor.org/packages/release/bioc/html/ballgown.html>`__
to combine data generated with DCC and circtest with ballgown-compatible
``stringtie`` output or cufflinks output converted via
`tablemaker <https://github.com/leekgroup/tablemaker>`__ in order get
deeper insights into differential exon usage within circRNA candidates.
enrich `(detailed documentation) <https://docs.circ.tools/en/latest/Enrichment.html>`__
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The ``enrichment`` module may be used to identify circRNAs enriched for
specific RNA binding proteins (RBP) based on DCC-identified circRNAs and
processed
`eCLIP <http://www.nature.com/nmeth/journal/v13/n6/full/nmeth.3810.html>`__
data. For K526 and HepG2 cell lines plenty of this data is available
through the
`ENCODE <https://www.encodeproject.org/search/?type=Experiment&assay_title=eCLIP>`__
project.
primer `(detailed documentation) <https://docs.circ.tools/en/latest/Primer.html>`__
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The ``primer`` command is used to design and visualize primers required
for follow up wet lab experiments to verify circRNA candidates.
.. |docs| image:: https://readthedocs.org/projects/circtools/badge/?version=latest
:alt: Documentation Status
:scale: 100%
:target: https://docs.circ.tools/en/latest/?badge=latest
.. |build| image:: https://github.com/jakobilab/circtools/actions/workflows/run_circtools_detect.yml/badge.svg?branch=master
:alt: CI Status
:scale: 100%
:target: https://github.com/jakobilab/circtools/actions/workflows/run_circtools_detect.yml
.. |docker| image:: https://github.com/jakobilab/circtools/actions/workflows/docker_multi_arch.yml/badge.svg?branch=master
:alt: Docker Images
:scale: 100%
:target: https://github.com/jakobilab/circtools/actions/workflows/docker_multi_arch.yml
.. |zenodo| image:: https://zenodo.org/badge/498448368.svg
:alt: Zenodo DOI link
:scale: 100%
:target: https://zenodo.org/badge/latestdoi/498448368
.. |downloads| image:: https://pepy.tech/badge/circtools
:alt: Python Package Index Downloads
:scale: 100%
:target: https://pepy.tech/project/circtools
.. |pypi| image:: https://badge.fury.io/py/circtools.svg
:alt: Python package version
:scale: 100%
:target: https://badge.fury.io/py/circtools
Raw data
{
"_id": null,
"home_page": "https://github.com/jakobilab/circtools",
"name": "circtools",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": null,
"keywords": "circRNA, circular RNA bioinformatics",
"author": "Tobias Jakobi",
"author_email": "tjakobi@arizona.edu",
"download_url": "https://files.pythonhosted.org/packages/32/e5/f142f527a6dceb53924ccfcd865d486ad27bb4bc74400cd39fe113380abe/circtools-2.0.tar.gz",
"platform": null,
"description": "**circtools**\n======================================================================\n\n**a one-stop software solution for circular RNA research**\n\n.. figure:: https://raw.githubusercontent.com/jakobilab/circtools/master/docs/img/circtools_200px.png\n :alt: circtools\n\nIntroduction\n-------------\n\nCircular RNAs (circRNAs) originate through back-splicing events from linear primary transcripts, are resistant to exonucleases, typically not polyadenylated, and have been shown to be highly specific for cell type and developmental stage. Although few circular RNA molecules have been shown to exhibit miRNA sponge function, for the vast majority of circRNAs however, their function is yet to be determined.\n\nThe prediction of circular RNAs is a multi-stage bioinformatics process starting with raw sequencing data and usually ending with a list of potential circRNA candidates which, depending on tissue and condition may contain hundreds to thousands of potential circRNAs. While there already exist a number of tools for the prediction process (e.g. `DCC <https://github.com/dieterich-lab/DCC>`__ and `CircTest <https://github.com/dieterich-lab/CircTest>`__), publicly available downstream analysis tools are rare.\n\nWe developed **circtools**, a modular, Python3-based framework for circRNA-related tools that unifies several functionalities in single command line driven software. The command line follows the `circtools subcommand` standard that is employed in samtools or bedtools. Currently, circtools includes modules for detecting and reconstructing circRNAs,\na quick check of circRNA mapping results, RBP enrichment screenings, circRNA primer design, statistical testing, and an exon usage module.\n\n\n\nDocumentation\n-------------\n\nClick `here <https://docs.circ.tools/>`__ to access the complete documentation on Read the Docs.\n\n\nInstallation\n------------\n\nVia docker [NEW in 2.0]\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nThe latest circtools docker version will be downloaded directly from GitHub. The container contains `all` dependencies required to run `circtools` except STAR and Bowtie.\n\n.. code-block:: console\n\n docker pull ghcr.io/jakobilab/circtools/circtools:latest\n\nAn bash alias to call circtools \"natively\" and skip the unwieldy full docker command is recommended:\n\n.. code-block:: console\n\n alias circtools='docker run --rm -v \"`pwd`\":/circtools/ ghcr.io/jakobilab/circtools/circtools'\n\nThis line can be added to the `.bashrc` or `.profile` file to be automatically loaded after login.\n\n\nVia pip\n~~~~~~~~~~~~~~~\n\n\nThe ``circtools`` package is written in Python 3 (supporting Python 3.8 - 3.12). It requires only a small number of external dependencies, namely standard bioinformatics tools:\n\n- `bedtools (>= 2.27.1) <https://bedtools.readthedocs.io/en/latest/content/installation.html>`__\n [RBP enrichment module, installed automatically]\n- `R (>= 4.0) <https://www.digitalocean.com/community/tutorials/how-to-install-r-on-ubuntu-22-04>`__\n [Data visualization and data processing]\n\nInstallation is managed through ``pip3 install circtools`` or ``python3 setup.py\ninstall`` when installed from the cloned GitHub repository. No sudo access is\nrequired if the installation is executed in an virtual environment which will install the\npackage in a user-writeable folder. The binaries should be installed\nto ``/home/$user/.local/bin/`` in case of Debian-based systems.\n\n``circtools`` was developed and tested on Debian Bookworm, but should also\nrun with any other distribution.\n\nThe installation can be performed directly from PyPi:\n\n.. code-block:: console\n\n # create virtual environment\n python3 -m venv circtools\n\n # activate virtual environment\n source circtools/bin/activate\n\n # install circtools\n pip install numpy # required for HTSeq, dependency of circtools\n pip install circtools\n\n # install R packages for circtools\n circtools_install_R_dependencies\n\nVia git (development version)\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nAdditionally, this repository offers the latest development version:\n\n.. code-block:: console\n\n pip install numpy # required for HTSeq, a dependency of circtools\n pip install git+https://github.com/jakobilab/circtools.git\n\nThe primer-design module as well as the exon analysis and circRNA testing module\nrequire a working installation of `R <https://cran.r-project.org/>`__ with\n`BioConductor <https://www.bioconductor.org/install/>`__. All R packages\nrequired can be automatically installed during the setup. Please see the\n`\"Installing circtools\" <http://docs.circ.tools/en/latest/Installation.html>`__\nchapter of the main circtools documentation for more detailed installation instructions.\n\n\nModules\n-------\n\nCirctools currently offers the following modules:\n\nnanopore `(detailed documentation) <https://docs.circ.tools/en/latest/Nanopore.html>`__ [NEW in 2.0]\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nRecent advances in long-read sequencing technologies have enabled the generation of\nfull-length circRNA sequences. The module is based on\n`long_read_circRNA <https://github.com/omiics-dk/long_read_circRNA>`__ and designed to specifically process the\nunique characteristics of Oxford Nanopore data, i.e. the handling of sequencing\nreads > 5kb, and provides accurate and efficient detection of circRNAs.\n\n\npadlock `(detailed documentation) <https://docs.circ.tools/en/latest/Conservation.html>`__ [NEW in 2.0]\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nSpatial transcriptomics emerged as a powerful technique to map the localization of\nsingle molecules to the level of individual cells and even offer subcellular resolution.\nAlthough most of the high-throughput methods were designed with linear polyadenylated\nRNAs in mind, some methods could target circRNAs as well. This module is\nspecifically tailored to the Xenium platform as it offers subcellular resolution\nand an option for custom panel design. The module requires three inputs: 1)\ncircRNA coordinates detected using \\textit{circtools}' detect step, 2)\na genome FASTA file, and 3) a transcriptome GTF file.\n\n\nconservation `(detailed documentation) <https://docs.circ.tools/en/latest/Conservation.html>`__ [NEW in 2.0]\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nEvolutionary conservation analysis oftentimes uncovers the potential\nfunctional relevance of circRNAs by comparing their sequence and genomic\nposition across different organisms. We developed the conservation module\nto enable users to perform circRNA conservation analysis in five widely\nstudied animal model species: mouse, human, rat, pig, and dog. The framework\nof the conservation module was developed with the flexibility to incorporate\nmore species in the analysis by simply adding the species to the input config file.\n\n\ndetect/metatool `(detailed documentation) <https://docs.circ.tools/en/latest/Detect.html>`__ [Updated in 2.0]\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nThe ``detect`` command is an interface to\n`DCC <https://github.com/dieterich-lab/DCC>`__, developed at the\nDieterich Lab. The module allows to detect circRNAs from RNA sequencing\ndata. The module is the foundation of all other steps for the circtools\nwork flow. All parameters supplied to circtools will be directly passed\nto DCC. The detect module also performs the new metatool functionality\nadded with circtools 2.0 which enables the addition of circRNA counts\ngenerated with `ciriquant` to further improve recall rates.\n\nquickcheck `(detailed documentation) <https://docs.circ.tools/en/latest/Quickcheck.html>`__\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nThe quickcheck module of circtools is an easy way to check the results\nof a DCC run for problems and to quickly assess the number of circRNAs\nin a given experiment. The module needs the mapping log files produced\nby STAR as well as the directory with the DCC results. The module than\ngenerates a series of figures in PDF format to assess the results.\n\nreconstruct `(detailed documentation) <https://docs.circ.tools/en/latest/Reconstruct.html>`__\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nThe ``reconstruct`` command is an interface to\n`FUCHS <https://github.com/dieterich-lab/FUCHS>`__. FUCHS is employing\nDCC-generated data to reconstruct circRNA structures. All parameters\nsupplied to circtools will be directly passed to FUCHS.\n\ncirctest `(detailed documentation) <https://docs.circ.tools/en/latest/Circtest.html>`__\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nThe ``circtest`` command is an interface to\n`CircTest <https://github.com/dieterich-lab/CircTest>`__. The module a a\nvery convenient way to employ statistical testing to circRNA candidates\ngenerated with DCC without having to write an R script for each new\nexperiment. For detailed information on the implementation itself take a\nlook at the `CircTest\ndocumentation <https://github.com/dieterich-lab/CircTest>`__. In\nessence, the module allows dynamic grouping of the columns (samples) in\nthe DCC data.\n\nexon `(detailed documentation) <https://docs.circ.tools/en/latest/Exon.html>`__\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nThe exon module of circtools employs the `ballgown R\npackage <https://www.bioconductor.org/packages/release/bioc/html/ballgown.html>`__\nto combine data generated with DCC and circtest with ballgown-compatible\n``stringtie`` output or cufflinks output converted via\n`tablemaker <https://github.com/leekgroup/tablemaker>`__ in order get\ndeeper insights into differential exon usage within circRNA candidates.\n\nenrich `(detailed documentation) <https://docs.circ.tools/en/latest/Enrichment.html>`__\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nThe ``enrichment`` module may be used to identify circRNAs enriched for\nspecific RNA binding proteins (RBP) based on DCC-identified circRNAs and\nprocessed\n`eCLIP <http://www.nature.com/nmeth/journal/v13/n6/full/nmeth.3810.html>`__\ndata. For K526 and HepG2 cell lines plenty of this data is available\nthrough the\n`ENCODE <https://www.encodeproject.org/search/?type=Experiment&assay_title=eCLIP>`__\nproject.\n\nprimer `(detailed documentation) <https://docs.circ.tools/en/latest/Primer.html>`__\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nThe ``primer`` command is used to design and visualize primers required\nfor follow up wet lab experiments to verify circRNA candidates.\n\n\n.. |docs| image:: https://readthedocs.org/projects/circtools/badge/?version=latest\n :alt: Documentation Status\n :scale: 100%\n :target: https://docs.circ.tools/en/latest/?badge=latest\n\n.. |build| image:: https://github.com/jakobilab/circtools/actions/workflows/run_circtools_detect.yml/badge.svg?branch=master\n :alt: CI Status\n :scale: 100%\n :target: https://github.com/jakobilab/circtools/actions/workflows/run_circtools_detect.yml\n\n.. |docker| image:: https://github.com/jakobilab/circtools/actions/workflows/docker_multi_arch.yml/badge.svg?branch=master\n :alt: Docker Images\n :scale: 100%\n :target: https://github.com/jakobilab/circtools/actions/workflows/docker_multi_arch.yml\n\n.. |zenodo| image:: https://zenodo.org/badge/498448368.svg\n :alt: Zenodo DOI link\n :scale: 100%\n :target: https://zenodo.org/badge/latestdoi/498448368\n\n.. |downloads| image:: https://pepy.tech/badge/circtools\n :alt: Python Package Index Downloads\n :scale: 100%\n :target: https://pepy.tech/project/circtools\n\n.. |pypi| image:: https://badge.fury.io/py/circtools.svg\n :alt: Python package version\n :scale: 100%\n :target: https://badge.fury.io/py/circtools\n",
"bugtrack_url": null,
"license": "GNU General Public License (GPL)",
"summary": "circtools - a circular RNA toolbox",
"version": "2.0",
"project_urls": {
"Bug Reports": "https://github.com/jakobilab/circtools/issues",
"Documentation": "https://docs.circ.tools",
"Homepage": "https://github.com/jakobilab/circtools",
"Jakobi Lab": "https://jakobilab.org",
"Source": "https://github.com/jakobilab/circtools"
},
"split_keywords": [
"circrna",
" circular rna bioinformatics"
],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "7c29646138653e979b5367f33cca90b6c0dc298169cdf0d8536d0c098bbce03b",
"md5": "96604b9c28e1cb70830c64584feb552b",
"sha256": "070dfc99f6a047bbf308118c51708dfbe60c0342898f6ec428c3a9c320efa3a7"
},
"downloads": -1,
"filename": "circtools-2.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "96604b9c28e1cb70830c64584feb552b",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8",
"size": 1118405,
"upload_time": "2025-02-17T02:14:25",
"upload_time_iso_8601": "2025-02-17T02:14:25.552884Z",
"url": "https://files.pythonhosted.org/packages/7c/29/646138653e979b5367f33cca90b6c0dc298169cdf0d8536d0c098bbce03b/circtools-2.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "32e5f142f527a6dceb53924ccfcd865d486ad27bb4bc74400cd39fe113380abe",
"md5": "bdaf22dffd6ef10d6d5f93e0f6700dbf",
"sha256": "605efb67fd8e8af6470d534d3b9d52e1a7d43f8436788e1faa294bea7e0e5381"
},
"downloads": -1,
"filename": "circtools-2.0.tar.gz",
"has_sig": false,
"md5_digest": "bdaf22dffd6ef10d6d5f93e0f6700dbf",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 1011788,
"upload_time": "2025-02-17T02:14:27",
"upload_time_iso_8601": "2025-02-17T02:14:27.869485Z",
"url": "https://files.pythonhosted.org/packages/32/e5/f142f527a6dceb53924ccfcd865d486ad27bb4bc74400cd39fe113380abe/circtools-2.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-02-17 02:14:27",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "jakobilab",
"github_project": "circtools",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "circtools"
}
JSON
