Non-DAPI Co-expression
Non-DAPI co-expression compares independently detected marker-positive populations.
It is different from DAPI-based co-expression because the two stainings do not share the same detected cell IDs.
How matching works
Each independent marker detection produces a mask of detected objects.
When co-expression is requested, NeuroQP compares the masks for the selected pair of marker detections.
Objects are treated as overlapping when their masks overlap above the configured threshold.
The overlap match is cached so repeated calculations can reuse the same result.
What positive means
For independent detection, positive means accepted marker-positive cell after classifier review.
Negative means rejected candidate and is not used as a marker-negative population.
Useful interpretations
Useful co-expression summaries include:
- marker A positive overlapping marker B positive
- marker A positive without marker B overlap
- marker B positive without marker A overlap
- either marker-positive population, counting overlaps once
Negative-negative co-expression is not meaningful for independent-detection projects.
Compare populations in Statistics
On desktop, open Statistics, choose Edit plots, and open a plot's editor. In the staining selector, choose the two independent-detection stainings and a supported co-expression mode. Add individual stainings as separate sources to compare them with the overlap population.
Start with positive/positive overlap. For example, compare accepted cFos cells, accepted TRAP cells and their matched overlap using marker-positive counts or marker-positive cells/mm².
Apply consistent animal, region and grouping settings, then save. If matching or pair statistics are missing or outdated, use Process statistics or Reprocess statistics and wait for completion.
Pair order determines which population is selected by an asymmetric mode. A positive/B negative selects accepted A cells without an accepted B match; it does not count rejected B detection candidates as a biological negative population.
See Co-expression analysis for the dashboard workflow and Metric semantics by workflow for metric interpretation.
Quality checks
Before interpreting non-DAPI co-expression, confirm that:
- both single-marker Results look trustworthy
- detections are well aligned in the same slice space
- atlas registration is good enough in the selected regions
- the overlap-based interpretation matches your biological question