Nomic Portal gives you a head start
Find the most variable proteins
Quickly highlight and rank proteins with the most variability across samples. Focus analysis on dynamic signals that often carry the most meaningful biological information.
Map global patterns across samples
Use UMAP to explore high-dimensional data by projecting samples into 2D space. Label points by any metadata to reveal clusters, gradients, and outliers linked to biological or experimental variables.
Compare conditions
Use volcano plots to compare conditions and highlight proteins with the largest and most significant differences. Visualize both effect size and statistical confidence to focus analysis on the most informative changes.
Create custom fold-change transformations
Define new comparisons by normalizing samples to reference groups or conditions. Use fold change to generate transformed datasets that highlight meaningful differences across cohorts.
Characterize protein response to dose
Use dose-response curves to quantify how proteins change across a range of perturbation concentrations. Identify thresholds for potency, efficacy, and toxicity to support mechanism-of-action or screening studies.
Cluster proteins and samples by similarity
Quickly highlight and rank proteins with the most variability across samples. Focus analysis on dynamic signals that often carry the most meaningful biological information.
Find the most variable proteins
Quickly highlight and rank proteins with the most variability across samples. Focus analysis on dynamic signals that often carry the most meaningful biological information.
Map global patterns across samples
Use UMAP to explore high-dimensional data by projecting samples into 2D space. Label points by any metadata to reveal clusters, gradients, and outliers linked to biological or experimental variables.
Compare conditions
Use volcano plots to compare conditions and highlight proteins with the largest and most significant differences. Visualize both effect size and statistical confidence to focus analysis on the most informative changes.
Create custom fold-change transformations
Define new comparisons by normalizing samples to reference groups or conditions. Use fold change to generate transformed datasets that highlight meaningful differences across cohorts.
Characterize protein response to dose
Use dose-response curves to quantify how proteins change across a range of perturbation concentrations. Identify thresholds for potency, efficacy, and toxicity to support mechanism-of-action or screening studies.
Cluster proteins and samples by similarity
Use clustergrams with unsupervised clustering to organize proteins and samples by similarity. Discover co-regulated groups, sample subtypes, and global patterns without prior assumptions.
Easy High Dimensional Visuals
Dynamically slice, filter, compare, and visualize complex datasets—easily uncovering patterns, outliers, and trends
Curated Data Pipelines
Access ready-to-use plots labelled and organized with provided metadata, powering intuitive data pipelines
Rapid Time to Insights
Quickly identify phenotypes and biomarkers of interest to quickly test, refine, and iterate
Solutions that adapt to your science, not the other way around
Omni 1000
Discover using 1000 of the most informative proteins in one product with absolute quantification, expertly curated to balance the critical must-haves, proteome-wide breadth, and real-world utility.
Core
Perform targeted discovery using context-specific, ~300-protein panels that bring together the most important proteins for that area.
Flex
À la carte selection of markers from the full library. Building a custom panel that is aligned with your study goals, without the usual restrictions.
Protein Target Library
Expertly curated to balance the critical must-haves, biological breadth, and real-world utility.
End-to-End Services
Explore the most extensive protein profiling services.