NeuroQP Docs

Co-expression Analysis

Co-expression analysis compares two stainings together instead of interpreting each staining separately.

The correct interpretation depends on how cells were detected.

DAPI or nuclei-source workflows

In cell counting and classification projects, both marker classifiers use the same shared cell population from the Cell Detection marker.

That means co-expression can compare ON/OFF states for the same detected cell IDs.

Common modes include:

  • ON / ON: cells expressing both markers
  • ON / OFF: cells expressing the first marker but not the second
  • OFF / ON: cells expressing the second marker but not the first
  • OFF / OFF: cells expressing neither marker
  • EITHER: cells expressing one marker or both

Independent-detection workflows

In independent-detection projects, each marker has its own detections. Cell IDs are not shared across stainings.

NeuroQP therefore uses mask-overlap matching to compare marker detections. It checks whether accepted marker-positive detections from two stainings overlap enough to be treated as the same biological cell or object.

For these workflows, co-expression should be interpreted as marker-positive overlap between independently detected populations.

Useful modes include:

  • marker A positive overlapping marker B positive
  • marker A positive without an overlapping marker B positive cell
  • marker B positive without an overlapping marker A positive cell
  • either marker-positive population, counting overlaps once

OFF/OFF is not meaningful for independent-detection projects because OFF means rejected candidate, not a biological negative class.

Before you calculate

Co-expression is only meaningful if both stainings are individually trustworthy first.

Before using it, make sure:

  • both selected models look reliable in Results
  • registration is good enough in the regions being compared
  • the comparison matches a real biological question

Practical workflow

  1. Review each staining individually in Results.
  2. Choose a pair based on a clear hypothesis.
  3. Use ON / ON or marker-positive overlap as the starting point.
  4. Interpret asymmetric modes only when they answer a specific population question.
  5. Compare co-expression output with the single-staining summaries.