Single Cell Analysis, Made Simple

OMIQ’s cloud-powered platform eliminates crashes, lag, and hardware limitations, allowing seamless analysis of massive datasets from any computer. With cloud storage and parallel computing, you can run multiple analyses at once—boosting productivity while OMIQ handles the heavy lifting.

Easily invite colleagues and assign roles with customizable permission levels. Share not just results, but the full context behind them — including datasets and workflows. Whether you're collaborating on analysis steps or reviewing outcomes, OMIQ makes it simple to share the entire process, securely and seamlessly.

Fully integrated clustering, dimension reduction, normalization, differential expression, trajectory, and data cleaning eliminate the need for external tools, ensuring seamless, reproducible analysis.

OMIQ’s traceable workflows ensure reproducibility, automation, and collaboration. Every action is recorded for auditing and sharing, while real-time updates enable flexible, structured, and exploratory analyses without delays.

OMIQ offers powerful integrated tools for dimensionality reduction, including t-SNE, opt-SNE, t-SNE-CUDA, UMAP, PCA, EmbedSOM, FIt-SNE, TriMap, Isomap, PaCMAP and PHATE. With opt-SNE, you can eliminate guesswork in parameter settings and consistently achieve great results.

Automatically categorize data with algorithms including FlowSOM, Phenograph, PARC, SPADE. ClusterX and DensVM. Virtual concatenation simplifies analysis, while graphs and heatmaps reveal patterns and relationships.

Cut through the noise and uncover what matters with OMIQ’s powerful statistical methods and visualizations using SAM, edgeR, Citrus or diffcyt. Identify the strongest stratifying signals aligned with your clinical or experimental metadata, enabling you to focus on the most relevant insights for your analysis.

Discover and visualize cellular development pathways with OMIQ’s trajectory inference tools including Wanderlust, Wishbone, Isomap and PHATE. Identify differentiation switch points and understand cell fate transitions to gain deeper insights into cellular processes.

Everything starts with clean data. Incorporate algorithms such as flowAI, flowCut and PeacoQC into your workflow to help automate and standardize this key step of analysis.

Tame batch effects and other unwanted signal differences between files in order to improve comparability for analysis and visualization. Natively integrated algorithms include fdaNorm, gaussNorm, CytoNorm and CyCombine.