OncoMark 1.0.0

A deep learning tool designed to predict Cancer Hallmark activities from tumor biopsy samples.

OncoMark

OncoMark is a Python package designed to systematically quantify hallmark activity using transcriptomics data from routine tumor biopsies. Ideal for applications in oncology research, personalized medicine, and biomarker discovery.

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Installation

Install OncoMark using pip:

pip install OncoMark

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Documentation

Comprehensive documentation is available at:
OncoMark Documentation

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Usage

Python API

import pandas as pd
from OncoMark import predict_hallmark_scores

# Load input data as a pandas DataFrame. Genes must be in column.
input_data = pd.read_csv('input_data.csv', index_col=0)

# Predict hallmark scores
predictions = predict_hallmark_scores(input_data)

# Display the predictions
predictions

Web Server

OncoMark also provides a web server for easy interaction.

Access the Online Web Server

You can use the hosted web server directly:

OncoMark Web Server

Suggestions

We welcome suggestions! If you have any ideas or feedback to improve OncoMark, please reach out to Shreyansh Priyadarshi.

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