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ROSALIND brings transparency to nCounter data analysis by letting you visualize how parameter choices, such as low-expression filtering and normalization methods, affect results before finalizing the analysis. Adjust thresholds in real time and immediately see the impact on quality metrics, differential expression, and biological interpretation.
ROSALIND’s Meta-Analysis engine applies machine learning to identify shared and unique signatures across differential expression studies to uncover patterns across experiments. Detect consistent biomarkers, highlight condition-specific effects, and accelerate hypothesis generation with integrated cross-study insights.
ROSALIND enables precise comparison of nCounter datasets and integration with multi-omics data to identify expression and regulatory patterns. This approach positions nCounter results within broader biological systems, supporting deeper interpretation and future data mining.
Go beyond the limits of nSolver. Enhance targeted gene panel analysis with AI-guided insights that reveal deeper biological meaning and surface patterns across public and private nCounter datasets.
Leverage built-in literature intelligence. Instantly access peer-reviewed publications related to your genes of interest to support interpretation, validation, and downstream decisions.
Cloud-native collaboration, built for science. Instantly share experiments, results, and annotations with collaborators around the world. No more plot-version chaos or buried email threads.
Unmatched nCounter expertise. Work with a team of PhD scientists, including nanoString experts who bring over 15 years of hands-on experience in instrumentation, chemistry, and data interpretation.