Combined RNA and ATAC Footprint Training of Gene Regulatory Network
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Updated
Sep 4, 2026 - R
Combined RNA and ATAC Footprint Training of Gene Regulatory Network
Reference mapping for single-cell genomics
Oxbow makes genomic data ready for high-performance analytics.
SDRF: The Proteomics sample metadata: Standard for experimental design annotation in proteomics datasets
Intuitive guide to multi-omics integration with toy examples: supervised latent components (DIABLO), unsupervised shared/partial/unique structure (DIVAS), VAEs/conditional VAEs, and key baselines (MOFA, JIVE, SNF) with practical tips + code.
𝒫robabilistic modeling of RNA velocity ⬱
scMEGA: Single-cell Multiomic Enhancer-based Gene regulAtory network inference
SDRF official validator and converts SDRF to pipeline configuration files
A novel method for single-cell diagonal integration: scConfluence
Precision Medicine MCP Platform: A set of bioinformatics servers + tools - production multiomics/genomics + spatial transcriptomics. Examples for ovarian cancer, breast cancer and preventative cardiovascular conditions
SIMBA: SIngle-cell eMBedding Along with features
Plain-language guide to causal inference for microbiome & multi-omics: DAGs/backdoor, confounders vs mediators/colliders, causal mediation (ACME/ADE/Total), and Double Machine Learning (DML) with toy examples + code.
GenoCraft: A Comprehensive, User-Friendly Web Platform for High-Throughput Omics Data Analysis and Visualization (https://arxiv.org/pdf/2312.14249)
MerCat2: python code for versatile k-mer counting and diversity estimation for database independent property analysis for metaome data
This repository contains different scripts to automate and visualize analysis performed for the "Integration of proteomics with genomics and transcriptomics increases the diagnosis rate of Mendelian disorders"
Exploring multicellular coordination from single-cell gene expression / multi-omics using mutlilayer network representations
Regional Association of DNA Methylome variability with the Exposome and geNome (RAMEN) is an R package which goal is to identify Variable Methylated Loci (VML) in microarray DNA methylation data. Then, using genome (G) and exposome (E) data, it can identify which individual (G or E) or joint (G+E or GxE) model better explains the VML variability.
MOVIS: A Multi-Omics Software Solution for Multi-modal Time-Series Clustering, Embedding, and Visualizing Tasks, by Aleksandar Anžel, Dominik Heider, and Georges Hattab
MOKA Snakemake pipeline for GWAS incorporating user provided multi-omics data sources such as gene expression, neural network weights, transcription factor binding, and evolutionary conservation scores.
Github repository for nanoSPLITS manuscript data and R scripts
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