AnnotationTransform
The software provides a training model function, users can use scRNA data as input, using random forest algorithm to train the model. By selecting and adjusting different parameters and features, users can optimize the performance of the model according to their research needs. Once the model is trained, the software allows users to use the trained model to make predictions on new scATAC data. scATAC data can be entered into the software, processed and analyzed by the model, and predicted results can be obtained. The software provides model evaluation capabilities to help users evaluate the performance and accuracy of trained models, as well as visualization capabilities.
1 maintainer
Metadata
1 maintainer
Release files for AnnotationTransform 1.0.0
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 | |
|---|---|---|---|---|
| annotationtransform-1.0.0.tar.gz | 6.3 kB | Without provenance | Details |
Release files / annotationtransform-1.0.0.tar.gz
| Download URL | annotationtransform-1.0.0.tar.gz |
|---|---|
| Size | 6.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
665d0784c222a0348123c5ff215a1721cb1e02d025626bee7d696944fdcd90c5
|
|
BLAKE2b-256 checksum How to use checksums |
7fb796f7561fbd585589b21cb0cd1a89d3105e0e498c8d02b95b16786fc6effd
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.10.9
|
Security for AnnotationTransform 1.0.0
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.
