This repository contains the code necessary to reproduce the work in our paper Interpretable and Integrative Analysis of Single-Cell Multiomics with scMKL. See the description below.
scMKL is now a package! Check out the package repository on GitHub for installation instructions.
This directory contains the scripts used to run XGBoost, MLP, and SVM for comparing to scMKL classification performance.
This directory contains the scripts used to run scMKL, EasyMKL, XGBoost, MLP, and SVM for resource usage comparisons.
This directory contains all the environments used to generate data for our publication.
If you use scMKL in your research, please cite using:
Kupp, S., VanGordon, I., Gönen, M., Esener, S., Eksi, S., Ak, C. Interpretable and integrative analysis of single-cell multiomics with scMKL. Commun Biol 8, 1160 (2025). https://doi.org/10.1038/s42003-025-08533-7
Our Shiny for Python application for viewing data produced from this work can be found here: scMKL_analysis