semvec/pypi-packages huggingface dataset:
FOXREG 0.1.2
A toolkit for regulatory comparison using AUCell and RSS
Requires Python: >=3.7


---
Let me know if you need further customization or changes! Email: mapostol@unmc.edu

# FOX: **F**unctional OMIC  e**X**ploration of Gene Regulatory Networks

FOX is a highly **modular** and **flexible** methodology for analyzing and comparing gene-regulatory networks, especially in single-cell gene expression data. It integrates several advanced tools, including **SCENIC**, **NMF**, and **Kendall's Tau**, to provide deep insights into gene regulation. FOX can be used to visualize, compare, and analyze the structure and activity of gene regulatory networks under different conditions.

[📘 Website Documentation](https://howard-fox-lab.github.io/FOX-Functional-OMIC-eXploration/)


## Installation (test)

	pip install FOXREG

## Usage

To run FOX, you'll need to prepare your data (such as RSS matrices and metadata) and pass it to the class. Here's an example of how to initialize and use FOX:

```python
        data = pd.read_csv("QA_QC_PBMC_rss_values_Feb3.csv") ## this would be one comparison (RSS)
        df_RAS = pd.read_csv("obj_AUC_metadata2_PBMC.csv") ## grab this from your SCENIC stuff, include ALL METADATA AUC AND cellLabels

        labels = data.columns[1:].tolist()

        # your new labels here is your "tissue" or "cell" column
        comparison = ComparisonTree("Naive CD4 T", df_RAS, "newLabels", data, labels, "Unnamed: 0", "3.5_AUCellThresholds_Info_PVMC_QA_QC.tsv")


        comparison.construct_tree() 
        p_vals = comparison.plotRSS_NMF("B", drawQuadrants=True, include_pvals=True)
        comparison.plot_3dEmbedding(rawRSS=False)
        comparison.analyze_factors("B", percentages=True)
        comparison.compareLayers("B", "Naive CD4 T", 0.055)
        tr = comparison.create_global_tree()
        tree, dict = tr

```


### Example Workflow:
1. **Prepare your single-cell gene expression data** (e.g., CSV format).
2. **Initialize FOX** with the necessary data, including control and treatment conditions.
3. **Compare gene-regulatory layers** across conditions using the `compareLayers` function.
4. **Visualize the network structure** using 2D and 3D plots.
5. **Assess the reproducibility** of the regulatory network using the global tree structure.
6. **Analyze factors and clusters** with advanced statistical methods and visualize the results.

## Contributions

Contributions are welcome! Feel free to fork the repository and submit pull requests for bug fixes, new features, or improvements. Help us improve FOX!

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
---
asrbench-cli 0.1.0
A command-line tool for the ASRBench framework, simplifying audio transcription system benchmarking with a single config file, supporting popular and custom transcription systems
Requires Python: <4.0,>=3.12

[:brazil: Versão Português Brasileiro](./README-pt.md)

# Asrbench-Cli
[//]: # (![python]&#40;https://img.shields.io/badge/Python-3776AB?style=for-the-badge&logo=python&logoColor=white&#41;)
[//]: # (![pypi package version]&#40;https://img.shields.io/pypi/pyversions/:asrbench-cli?style=for-the-badge&#41;)

## Introduction
ASRBench CLI is a complementary tool to the [ASRBench](https://github.com/ASRBench/asrbench) framework, designed 
to simplify the execution of audio transcription system benchmarks directly from the command line.

With it, you can:

- Use the most popular transcription systems on the market.
- Add new customized transcription systems.
- Run benchmarks simply, using just one configuration file.

## Installation
To install ASRBench, all you need is [Python 3.12+](https://www.python.org/downloads/) and pip. Use the
command below to install the latest version:

```sh
pip install asrbench-cli
```

> [!NOTE]
> The list of project dependencies is available in the file [pyproject.toml](https://github.com/ASRBench/asrbench-cli/blob/main/pyproject.toml)

## Usage
The CLI requires a configuration file to work, in the same format as the framework. 
benchmark environment, defining datasets, transcribers and output parameters in a simple and declarative way. 
declarative. For more details on the structure of the configuration file, go to
[documentation](https://asrbench.github.io/asrbench/cli/installation).

Below is an example of the configuration file structure:

```yaml
# data output configuration
output:
  type: "csv"
  dir: "./results"
  filename: "example_filename"

# datasets configuration
datasets:
  dataset1:
    audio_dir: "resources/common_voice_05/wav"
    reference_dir: "resources/common_voice_05/txt"

# transcription system configuration
transcribers:
  faster_whisper_medium_int8:
    asr: "faster_whisper"
    model: "medium"
    compute_type: "int8"
    device: "cpu"
    beam_size: 5
    language: "en"  
```

With the configuration file in hand, just run the command:

```sh
asrbench-cli run path/to/configfile.yml
```
The CLI will read the configuration file, set up the benchmark and run it automatically. All progress and steps 
will be displayed directly in the terminal, including the percentage of completion and a time estimate for the 
completion of each stage of the transcription process.

> [!TIP]
> For a complete list of available commands and instructions for more advanced uses, see [documentation](https://asrbench.github.io/asrbench/cli/usage).

## License
Distributed under the MIT license. See the [LICENSE](https://github.com/ASRBench/asrbench-cli/blob/main/LICENSE) file for more details.