SpatialCorr-sim is a set a Python framework for simulating spatial transcriptomics data with spatially varying correlation across the slide. Specifically, this framework takes as input a spatial transcriptomics dataset and uses this dataset to “seed” simulated datasets. That is, simulated datasets are generated such that the marginal distribution of UMI counts match those in the input dataset, but the correlation between genes can be specified by the user.Moreover, this package contains a framework for generating random patterns of spatially varying correlation among a set of genes. Altogether, SpatialCorr-sim can be used for the evaluation of computational methods that analyze the correlation among genes in spatial transcriptomics data.
For instructions on installing and running SpatialCorr-sim, see the GitHub repository: https://github.com/mbernste/SpatialCorr-sim
Metadata
Release files for spatialcorr-sim 0.0.1
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-sim-0.0.1.tar.gz | 2.1 MB | Without provenance | Details for spatialcorr-sim-0.0.1.tar.gz |
Release files / spatialcorr-sim-0.0.1.tar.gz
| Download URL | spatialcorr-sim-0.0.1.tar.gz |
|---|---|
| Size | 2.1 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
8d06528ce3dd7e5d30fd82663589740fd0f104bea410a1308f11d9191a553328
|
|
BLAKE2b-256 checksum How to use checksums |
437ac5436f25aae531929916816d9cea62f9aa6b2aa170cc438717de31e0853b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.5.0 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.24.0 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.7.8
|
Security for spatialcorr-sim 0.0.1
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.