NeuroQP Docs

Statistics Overview

Statistics turns slice-level Results into comparisons across animals, groups, conditions, brain regions, and stainings.

Use Statistics after the underlying Results look trustworthy.

What Statistics is for

Statistics helps answer study-level questions such as:

  • Which groups differ in a selected region?
  • Does one staining show a stronger regional pattern than another?
  • Are differences driven by counts, proportions, or density?
  • How do patterns look across anatomy?

Before calculating statistics

Make sure that:

  • staining and model selections are correct
  • slice-level output looks reasonable in Results
  • selected brain regions are appropriate for the question

For registered projects, make sure processing and registration are complete enough for interpretation.

For Detail only projects, make sure slice brain-region assignments and pixel size are correct before interpreting density or region-level summaries.

Metrics depend on source kind

For shared cell detection projects, Statistics can use total cells, ON cells, OFF cells, % ON, and density metrics.

For independent marker detection projects, Statistics uses accepted marker-positive cells, area, and marker-positive cells/mm2.

Independent marker detection projects do not support % ON or all-cell density because there is no shared all-cell denominator.

Recalculate after analysis changes

If the underlying model, registration, slice inclusion, selected regions, or direct brain-region assignment changes, previously calculated summaries may no longer reflect the current project state.

Recalculate statistics after meaningful changes.

Plot families

Statistics supports:

  • Heatmaps for broad animal-by-region pattern scans
  • Bar plots for group mean summaries and variability
  • Dot/strip plots for individual animal values
  • Box/violin plots for distribution shape, spread, and medians
  • Effect-size plots for standardized group differences against a baseline
  • Scatter plots for relationships between two selected metrics
  • Mirrored plots for side-by-side comparison of two metrics
  • Anatomical representations for mapping values back onto brain regions

Choose the metric and plot type based on the biological question.