# AI-based Cancer Stem Cell profiler and Neoplasia Deconvoluter (ACSCeND)

**ACSCeND** is a Python package designed to analyze and process stem cell transcriptomics data. It includes two core modules for predicting stem cell subtypes and deconvoluting bulk RNA-seq data using deep learning.

## Features

1. **Stem Cell Subtypes Predictor**  
   Identify stem cell subtypes — Pluripotent, Multipotent, or Unipotent — from single-cell stem cell transcriptomics data.

2. **Deep Learning-based Deconvoluter**  
   Deconvolute bulk RNA-seq data into meaningful components using cutting-edge deep learning techniques.

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## Installation

Install ACSCeND using pip:

```bash
pip install ACSCeND
```

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## Documentation

Comprehensive documentation is available at:  
[ACSCeND Documentation](https://acscend.readthedocs.io/en/latest/)

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## Usage

### Stem Cell Subtypes Predictor

```python
from ACSCeND import Predictor

# Example usage
predictor = Predictor()
subtypes = predictor(input_data)
```

### Deep Learning-based Deconvoluter

```python
from ACSCeND import Deconvoluter

# Example usage
real_freq, real_gep = Deconvoluter(pseudo_data, sig_matrix, pseudo_freq, real_data, normalized=False)
```

For detailed examples and API reference, visit the [documentation](https://acscend.readthedocs.io/en/latest/).

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## Suggestions

We welcome suggestions! If you have any ideas or feedback to improve ACSCeND, please reach out to [Shreyansh Priyadarshi](mailto:shreyansh.priyadarshi02@gmail.com).

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