CNSistent

Name	CNSistent JSON
Version	0.7.1 JSON
	download
home_page	None
Summary	Tools for imputation, segmentation, analysis, and plotting of Copy Number Segments (CNS).
upload_time	2024-12-16 23:53:45
maintainer	None
docs_url	None
author	None
requires_python	>=3.9
license	MIT
keywords	cns bioinformatics copy number segments genomics
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            ![CNSistent Logo](https://cnsistent.readthedocs.io/en/latest/_images/Logo.png)

[![PyPI version](https://badge.fury.io/py/CNSistent.svg)](https://badge.fury.io/py/CNSistent)
[![Documentation Status](https://readthedocs.org/projects/cnsistent/badge/?version=latest)](https://cnsistent.readthedocs.io/en/latest/?badge=latest)

CNSistent is a Python tool for processing and analyzing copy number data. It is designed to work with data from a variety of sources. The tool is designed to be easy to use, and to provide a comprehensive set of analyses and visualizations.

## [**READ THE DOCS HERE**](https://cnsistent.readthedocs.io/en/latest)

CNSistent can be used as a Python package, or downloaded together with the respective data (PCAWG, TRACERx, TCGA, genomic locations):

## Installation links


 1. [Full Bitbucket repository with ~1GB of data.](https://bitbucket.org/schwarzlab/cnsistent/src/main/REPOSITORY.md)
 2. [PIP package only.](https://pypi.org/project/cnsistent/)


### [LICENSE](https://bitbucket.org/schwarzlab/cnsistent/src/main/LICENSE.txt)
            

Raw data

            {
    "_id": null,
    "home_page": null,
    "name": "CNSistent",
    "maintainer": null,
    "docs_url": null,
    "requires_python": ">=3.9",
    "maintainer_email": "Adam Streck <adam.streck@gmail.com>",
    "keywords": "CNS, bioinformatics, copy number segments, genomics",
    "author": null,
    "author_email": "Adam Streck <adam.streck@gmail.com>",
    "download_url": "https://files.pythonhosted.org/packages/74/ed/a5088859916d22ee9a85cd75ea9cbd143441a31e31ad7c6f4c24eebe1ba4/cnsistent-0.7.1.tar.gz",
    "platform": null,
    "description": "![CNSistent Logo](https://cnsistent.readthedocs.io/en/latest/_images/Logo.png)\n\n[![PyPI version](https://badge.fury.io/py/CNSistent.svg)](https://badge.fury.io/py/CNSistent)\n[![Documentation Status](https://readthedocs.org/projects/cnsistent/badge/?version=latest)](https://cnsistent.readthedocs.io/en/latest/?badge=latest)\n\nCNSistent is a Python tool for processing and analyzing copy number data. It is designed to work with data from a variety of sources. The tool is designed to be easy to use, and to provide a comprehensive set of analyses and visualizations.\n\n## [**READ THE DOCS HERE**](https://cnsistent.readthedocs.io/en/latest)\n\nCNSistent can be used as a Python package, or downloaded together with the respective data (PCAWG, TRACERx, TCGA, genomic locations):\n\n## Installation links\n\n\n 1. [Full Bitbucket repository with ~1GB of data.](https://bitbucket.org/schwarzlab/cnsistent/src/main/REPOSITORY.md)\n 2. [PIP package only.](https://pypi.org/project/cnsistent/)\n\n\n### [LICENSE](https://bitbucket.org/schwarzlab/cnsistent/src/main/LICENSE.txt)",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "Tools for imputation, segmentation, analysis, and plotting of Copy Number Segments (CNS).",
    "version": "0.7.1",
    "project_urls": null,
    "split_keywords": [
        "cns",
        " bioinformatics",
        " copy number segments",
        " genomics"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "6b9a794f377b70de812e4d872523a69b551d32da062c4852eb5ec7184b5687bb",
                "md5": "b0dc8c65e204575d19d1c628e15c13c5",
                "sha256": "68b6a5ba3f43ef4f5aa8cef0774693895ea0748e9d636d2f5c89842cdc1220bf"
            },
            "downloads": -1,
            "filename": "cnsistent-0.7.1-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "b0dc8c65e204575d19d1c628e15c13c5",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.9",
            "size": 72016,
            "upload_time": "2024-12-16T23:53:38",
            "upload_time_iso_8601": "2024-12-16T23:53:38.951428Z",
            "url": "https://files.pythonhosted.org/packages/6b/9a/794f377b70de812e4d872523a69b551d32da062c4852eb5ec7184b5687bb/cnsistent-0.7.1-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "74eda5088859916d22ee9a85cd75ea9cbd143441a31e31ad7c6f4c24eebe1ba4",
                "md5": "25bf8fcc69f84320497408126436abb0",
                "sha256": "cc993d97dd7da740ce28d568e222ac59ad0642674aa9c8337fbe13bda0770e46"
            },
            "downloads": -1,
            "filename": "cnsistent-0.7.1.tar.gz",
            "has_sig": false,
            "md5_digest": "25bf8fcc69f84320497408126436abb0",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.9",
            "size": 28606704,
            "upload_time": "2024-12-16T23:53:45",
            "upload_time_iso_8601": "2024-12-16T23:53:45.326001Z",
            "url": "https://files.pythonhosted.org/packages/74/ed/a5088859916d22ee9a85cd75ea9cbd143441a31e31ad7c6f4c24eebe1ba4/cnsistent-0.7.1.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2024-12-16 23:53:45",
    "github": false,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "lcname": "cnsistent"
}