Single Cell Multi-omics deep clustering

MerCat2: python code for versatile k-mer counting and diversity estimation for database independent property analysis for metaome data

R package for visualising high-dimensional categorical data. Fully ggplot compatible implementation for the diceplot plotting library

Code for paper Multiomics dynamic learning enables personalized diagnosis and prognosis for pan-cancer and cancer-subtypes

Network Regression Embeddings reveal cell-type Transcription Factor coordination for target gene (TG) regulation

MOVIS: A Multi-Omics Software Solution for Multi-modal Time-Series Clustering, Embedding, and Visualizing Tasks, by Aleksandar Anžel, Dominik Heider, and Georges Hattab

An R package to perform differential network analysis in single and multi-omic data. It can also be used for feature selection in ML.

MOMSI Standard Landscape Review Curation Workflow & Multi-Omics Dashboard

Topology-based analysis and querying of short longitudinal multi-omics trajectories using Omics Trajectory Signatures (OTS)

Transcriptomic analysis of WNT/TGFβ/EMT signaling in epithelial ovarian cancer (EOC) datasets.

Computational drug repurposing for LUAD using TCGA + CMap + multi-omics integration.

Molecular Data Engineering and Multimodal Artificial Intelligence for Translational Biomedical Discovery

Multi-omics integration of kidney transcriptomics and urinary proteomics to explore fibrosis, metabolism, and inflammation in diabetic kidney disease (DKD)

Code for paper Multiomics dynamic learning enables personalized diagnosis and prognosis for pan-cancer and cancer-subtypes

Analysis code, scripts, and data visualization from my Master's thesis focused on the multiomic integration (transcriptomics, lipidomics, spatial lipidomics) of monoglyceride responses in adipose tissue macrophages within the context of obesity.

Graph Neural Networks with Multiple Prior Knowledge for Multi-Omics Data Analysis

Simulate and download multi-omics datasets, by selecting omics types, sample sizes, and other parameters.

Jupyter notebooks and supporting functions for analzying triomics data generated with MissionBio.

Snakemake workflow that integrates Xenium spatial transcriptomics with CODEX/PhenoCycler spatial proteomics on the same tissue micro-array slides: per-cell RNA and protein quantification, QC, totalVI-derived joint embedding and Leiden clustering for cell-type annotation. Runs on SLURM in an Apptainer container.

coxnnet v1 and v2 models updated to work with Python3.