Seamless Multi-Omics Integration for Instant Insights with Omics Playground
- Comprehensive functional analysis
- Enhanced biomarker discovery
- Improved prediction of genotype-phenotype response.
MULTIOMICS DATA ANALYSIS SOFTWARE
MultiOmics Data Types and Analyses
Data Types Supported
You can integrate the following omics data types using Omics Playground:
- Transcriptomics
- Proteomics
- Metabolomics
Similarity Network Fusion
Improve sample clustering by combining multiple omic types, and compare each layer's sample correlation heatmap side by side. Identify condition-specific modules that span several omics layers.
LASAGNA
Stack your omics layers into a single multi-layer graph and see how features correlate across them. Detect trait-specific biomarkers that are connected across multiple omics.
Multi-Omics Factor Analysis (MOFA)
Infer shared factors with MOFA, DIABLO, NMF, RGCCA and MCIA, and find those that correlate significantly with your phenotypes. Explore feature weights and centrality to pinpoint key genes, proteins or metabolites, and identify co-enriched gene sets and pathways.
Multi-Omics Supervised Auto-Encoder
Integrate your omics layers with semi-supervised autoencoders, run interactively and without code. Identify multi-omics biomarkers through feature importance, and check model quality with confusion matrices and reconstruction accuracy plots.
Multi-Omics GSEA
Find gene sets that are co-enriched across several omics with multi-GSEA scatterplots. Use pathway heatmaps to see phenotype-specific clustering, and view gene, protein and metabolite expression together on pathway diagrams.
Frequently asked questions
Omics Playground is a cloud-based platform that allows you and your team to easily explore, analyze, and visualize your RNA-Seq and proteomics data with just a few clicks.
Multi-omics data integration aims to harmonize multiple layers of biological data, such as transcriptomics, proteomics, metabolomics and epigenomics.
You can learn more about multi-omics and its challenges in our blog post on Key Challenges in Multi-Omics Data Integration.
