amlpy is a small-scale tool designed to analyze Affymetrix microarray data for detecting acute myeloid leukemia (AML). Utilizing several AI/ML methods, amlpy can assess mRNA microarray samples to determine the likelihood of them being cancerous.
amlpy offers several features designed to facilitate effective analysis and interpretation of microarray data:
Data Preprocessing: Automates the cleaning and normalization of Affymetrix microarray data to prepare it for analysis.
Machine Learning Model Training & Evaluation: Implements robust training procedures with cross-validation to optimize and evaluate predictive models.
Cancer Prediction Generation: Delivers predictions on the probability of AML presence in microarray samples
To get started with amlpy, follow these steps to set up the environment on your local machine:
- Clone the amlpy repo to your local machine using the following command:
git clone https://github.com/tuulu/amlpy.git
cd amlpy- Install all necessary Python packages listed in the requirements.txt file:
pip install -r requirements.txt- Please ensure you have the data downloaded first by running src/data_import.py as a standalone script
python src/data_import.py- Once the datasets are installed, start the pipeline by running .
python main.py- Enjoy!
Example outputs from running the pipeline can be found in /example_results