Dynamic Baseline live

Introducing the Dynamic Baseline feature, now available for high-dimensional datasets on app.teiko.bio, including spectral flow and mass cytometry. 

This feature allows users to set any time point, such as the start of lymphodepletion (e.g., C1D15), as the new baseline for normalization, providing more flexibility when analyzing longitudinal data across key clinical milestones.

Key Features:

Custom Baseline for Better Comparisons: Select any time point, like C1D15, as the baseline, allowing for more meaningful comparisons across phases of the study (e.g., between C1D15, C2D1, and C2D15).

Tailored Normalization: By choosing specific baseline points, users can better reflect biological changes during therapy, providing clearer insights into immune responses over time.

Updated Statistics for Normalization: FDR values automatically update when the selected baseline changes, ensuring accurate comparisons.

Indications when a timepoint has sufficient specimens to do comparisons: Endpoints with at least 3 samples will be marked in black, while those with an insufficient number of samples will be red.

How to Use:

Set baseline using the “Normalization Baseline” Dropdown: Select a specific time point, such as C1D15 (start of lymphodepletion), to serve as the baseline.

Normalization Output: Data will be normalized based on the selected baseline by subtracting each subject’s baseline value from their subsequent values. This adjustment allows for tracking of immune responses across all other time points by aligning population or marker values accordingly. Statistics will not be shown if the selected baseline value is included in the multi-group comparison.

This feature improves the ability to track immune responses at critical points during treatment, allowing for more precise comparisons between key dates, particularly when pivotal events like lymphodepletion are in the therapeutic process.