# SpatialCorr: Analyzing spatially varying correlation
 
## 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:

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).
Metadata
Release files for spatialcorr 1.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| spatialcorr-1.2.0.tar.gz | 12.9 MB | Without provenance | Details for spatialcorr-1.2.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| spatialcorr-1.2.0-py3-none-any.whl | Python 3 | none | any | Details for spatialcorr-1.2.0-py3-none-any.whl |
Total release size: 25.7 MB
Release files / spatialcorr-1.2.0.tar.gz
| Download URL | spatialcorr-1.2.0.tar.gz |
|---|---|
| Size | 12.9 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
7eb6f356637e8cb323b39dbde5e9fa9f88f790dee02b4d08f68307cfe851101e
|
|
BLAKE2b-256 checksum How to use checksums |
a043546991112da73440cd6f2a46d3e74a8f876de1a5d693806598ef5abfd1ae
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.15
|
Release files / spatialcorr-1.2.0-py3-none-any.whl
| Download URL | spatialcorr-1.2.0-py3-none-any.whl |
|---|---|
| Size | 12.9 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
1174a7f3abe9fdea76f4c242c7abc1707834dab07036e90131503c4140280dbe
|
|
BLAKE2b-256 checksum How to use checksums |
45c6290256feb2dfbaf96f44d4bae91948d710ff71f0b8376212bfa1c34cb9e1
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.15
|
Security for spatialcorr 1.2.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.