spatialcorr


Namespatialcorr JSON
Version 1.2.0 PyPI version JSON
download
home_pagehttps://github.com/mbernste/spatialcorr
SummarySpatialCorr
upload_time2023-01-25 15:28:57
maintainer
docs_urlNone
authorMatthew N. Bernstein
requires_python
licenseMIT License
keywords spatial-transcriptomics gene-expression computational-biology
VCS
bugtrack_url
requirements numpy pandas scipy anndata scikit-learn matplotlib seaborn statsmodels numpydoc
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # SpatialCorr: Analyzing spatially varying correlation 
  
![PyPI Version](https://img.shields.io/pypi/v/spatialcorr)
![Read the Docs](https://readthedocs.org/projects/spatialcorr/badge/?version=latest)

## About

SpatialCorr is a set of statistical methods for identifying genes whose correlation structure changes across a spatial transcriptomics sample. Along with a set of statistical tests, SpatialCorr also offers a number of methods for visualizing spatially varying correlation.

Here is a schematic overview of the analyses performed by SpatialCorr:

![alt text](https://raw.githubusercontent.com/mbernste/spatialcorr/main/imgs/Overview_MainFigure_V3-01.png)

For more details regarding the underlying method, see the paper:  
[Bernstein, M.N., Ni, Z., Prasad, A., Brown, J., Mohanty, C., Stewart, R., Newton, M.A., Kendziorski, C. (2022). SpatialCorr: Identifying gene sets with spatially varying correlation structure. *Cell Reports Methods*.](https://doi.org/10.1016/j.crmeth.2022.100369)

## Installation

To install SpatialCorr using Pip, run the following command:

`pip install spatialcorr`

## Usage

#### Documentation

For SpatialCorr's API manual, please visit the [documentation](https://spatialcorr.readthedocs.io/en/latest/index.html).

#### Tutorial

For a tutorial on running SpatialCorr, please see the [tutorial](https://github.com/mbernste/spatialcorr/blob/main/tutorial/SpatialCorr_tutorial.ipynb). This tutorial can also be run via [Google Colab](https://colab.research.google.com/drive/199gpNyyM6Jj8k9LLn1d71l_pX16yko60?usp=sharing).

            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/mbernste/spatialcorr",
    "name": "spatialcorr",
    "maintainer": "",
    "docs_url": null,
    "requires_python": "",
    "maintainer_email": "",
    "keywords": "spatial-transcriptomics,gene-expression,computational-biology",
    "author": "Matthew N. Bernstein",
    "author_email": "mbernstein@morgridge.org",
    "download_url": "https://files.pythonhosted.org/packages/a0/43/546991112da73440cd6f2a46d3e74a8f876de1a5d693806598ef5abfd1ae/spatialcorr-1.2.0.tar.gz",
    "platform": null,
    "description": "# SpatialCorr: Analyzing spatially varying correlation \n  \n![PyPI Version](https://img.shields.io/pypi/v/spatialcorr)\n![Read the Docs](https://readthedocs.org/projects/spatialcorr/badge/?version=latest)\n\n## About\n\nSpatialCorr is a set of statistical methods for identifying genes whose correlation structure changes across a spatial transcriptomics sample. Along with a set of statistical tests, SpatialCorr also offers a number of methods for visualizing spatially varying correlation.\n\nHere is a schematic overview of the analyses performed by SpatialCorr:\n\n![alt text](https://raw.githubusercontent.com/mbernste/spatialcorr/main/imgs/Overview_MainFigure_V3-01.png)\n\nFor more details regarding the underlying method, see the paper:  \n[Bernstein, M.N., Ni, Z., Prasad, A., Brown, J., Mohanty, C., Stewart, R., Newton, M.A., Kendziorski, C. (2022). SpatialCorr: Identifying gene sets with spatially varying correlation structure. *Cell Reports Methods*.](https://doi.org/10.1016/j.crmeth.2022.100369)\n\n## Installation\n\nTo install SpatialCorr using Pip, run the following command:\n\n`pip install spatialcorr`\n\n## Usage\n\n#### Documentation\n\nFor SpatialCorr's API manual, please visit the [documentation](https://spatialcorr.readthedocs.io/en/latest/index.html).\n\n#### Tutorial\n\nFor a tutorial on running SpatialCorr, please see the [tutorial](https://github.com/mbernste/spatialcorr/blob/main/tutorial/SpatialCorr_tutorial.ipynb). This tutorial can also be run via [Google Colab](https://colab.research.google.com/drive/199gpNyyM6Jj8k9LLn1d71l_pX16yko60?usp=sharing).\n",
    "bugtrack_url": null,
    "license": "MIT License",
    "summary": "SpatialCorr",
    "version": "1.2.0",
    "split_keywords": [
        "spatial-transcriptomics",
        "gene-expression",
        "computational-biology"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "45c6290256feb2dfbaf96f44d4bae91948d710ff71f0b8376212bfa1c34cb9e1",
                "md5": "83cb6e025b2bcb140d854b5a42f66fd1",
                "sha256": "1174a7f3abe9fdea76f4c242c7abc1707834dab07036e90131503c4140280dbe"
            },
            "downloads": -1,
            "filename": "spatialcorr-1.2.0-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "83cb6e025b2bcb140d854b5a42f66fd1",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": null,
            "size": 12872541,
            "upload_time": "2023-01-25T15:28:54",
            "upload_time_iso_8601": "2023-01-25T15:28:54.842986Z",
            "url": "https://files.pythonhosted.org/packages/45/c6/290256feb2dfbaf96f44d4bae91948d710ff71f0b8376212bfa1c34cb9e1/spatialcorr-1.2.0-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "a043546991112da73440cd6f2a46d3e74a8f876de1a5d693806598ef5abfd1ae",
                "md5": "3714175bc8258d10c9e3c762770a78de",
                "sha256": "7eb6f356637e8cb323b39dbde5e9fa9f88f790dee02b4d08f68307cfe851101e"
            },
            "downloads": -1,
            "filename": "spatialcorr-1.2.0.tar.gz",
            "has_sig": false,
            "md5_digest": "3714175bc8258d10c9e3c762770a78de",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 12867473,
            "upload_time": "2023-01-25T15:28:57",
            "upload_time_iso_8601": "2023-01-25T15:28:57.960040Z",
            "url": "https://files.pythonhosted.org/packages/a0/43/546991112da73440cd6f2a46d3e74a8f876de1a5d693806598ef5abfd1ae/spatialcorr-1.2.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2023-01-25 15:28:57",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "github_user": "mbernste",
    "github_project": "spatialcorr",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": false,
    "requirements": [
        {
            "name": "numpy",
            "specs": [
                [
                    ">=",
                    "1.19.5"
                ]
            ]
        },
        {
            "name": "pandas",
            "specs": [
                [
                    ">=",
                    "1.2.1"
                ]
            ]
        },
        {
            "name": "scipy",
            "specs": [
                [
                    ">=",
                    "1.4.1"
                ]
            ]
        },
        {
            "name": "anndata",
            "specs": [
                [
                    ">=",
                    "0.7.5"
                ]
            ]
        },
        {
            "name": "scikit-learn",
            "specs": [
                [
                    ">=",
                    "0.24.2"
                ]
            ]
        },
        {
            "name": "matplotlib",
            "specs": []
        },
        {
            "name": "seaborn",
            "specs": [
                [
                    ">=",
                    "0.11.1"
                ]
            ]
        },
        {
            "name": "statsmodels",
            "specs": [
                [
                    ">=",
                    "0.12.2"
                ]
            ]
        },
        {
            "name": "numpydoc",
            "specs": [
                [
                    ">=",
                    "1.1.0"
                ]
            ]
        }
    ],
    "lcname": "spatialcorr"
}
        
Elapsed time: 0.03337s