CONDUCTVISION MICROSCOPY · COLOCALIZATION

Quantitative fluorescence colocalization, ready for peer review.

Pearson r, Manders M1 / M2, and Costes randomization — computed per ROI across full cohorts. Threshold parameters logged with every output, so the methods section writes itself.

Pearson rManders M1 / M2Costes auto-thresholdROI batch

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coloc.scatter — DAPI · GFP · mCherry

Pearson r0.74

Manders M10.81

Manders M20.63

Pearson rLinear correlation across all pixels−1 ≤ r ≤ +1

Manders M1Fraction of CH1 signal overlapping CH20 ≤ M1 ≤ 1

Manders M2Fraction of CH2 signal overlapping CH10 ≤ M2 ≤ 1

Costes T₁/T₂Auto-threshold + randomization p-value1000 scrambles

CORE CAPABILITIES

Defensible co-occurrence, end to end

Pearson alone is not a colocalization claim. ConductVision pairs every metric with the threshold, ROI, and randomization context that reviewers now expect.

Multi-channel splitting

Auto-detect channel order from OME-TIFF and ND2 metadata. Bleed-through correction with linear unmixing for closely-spaced fluorophores. Works on confocal, light-sheet, and widefield.

OME-TIFF · ND2 · CZI

Costes auto-threshold

Removes the user-bias problem. T₁ and T₂ are derived from the regression line, then validated by 1000-scramble randomization for a publication-grade p-value against chance overlap.

Costes · Otsu · manual fallback

ROI co-occurrence

Restrict analysis to nuclei, cells, or atlas regions — not the whole image. Per-ROI Pearson r and Manders M1/M2, with population statistics across thousands of ROIs from a single field.

Per-cell · Per-region

Cohort statistical comparison

Group-level stats compare WT vs KO, treated vs control. Linear mixed models with subject as random effect, plus FDR-corrected pairwise tests across markers and conditions.

Mixed model · FDR

PIPELINE

From raw stack to publication-ready table in four steps

Load

Drop multi-channel OME-TIFF, ND2, or CZI. Channel order auto-detected from metadata. Reference channel marked for ROI.

Threshold

Costes algorithm derives T₁ and T₂ from the regression line. Manual or Otsu override available with full audit trail.

Quantify

Per-ROI Pearson r, Manders M1/M2, and Costes p-value. Population statistics aggregated across nuclei, cells, or atlas regions.

Export

CSV with full parameter log, scatter-plot PNG, and methods-section snippet citing the exact thresholds and randomization seed used.

CAPABILITY MATRIX

ConductVision vs ImageJ Coloc 2, JACoP, and commercial suites

Capability comparison only — not a benchmark. ImageJ and JACoP remain excellent for one-shot work; ConductVision is built for cohort scale.

Capability	ConductVision	ImageJ Coloc 2	JACoP	Commercial suites
Pearson r	Yes	Yes	Yes	Yes
Manders M1 / M2	Yes	Yes	Yes	Yes
Costes auto-threshold	Yes	Yes	Yes	Some
Costes randomization p-value	Yes	Yes	Limited	Some
Per-ROI batch (1000+ cells)	Yes	Manual	Manual	Per-license
Atlas-region restricted analysis	Yes	No	No	No
Cohort-level group statistics	Yes	No	No	Some
Headless CLI / batch mode	Yes	Limited	No	Add-on
Reproducible parameter log	Yes	Manual	Manual	Some

Capability comparison · cited per documentation as of 2026-04

METHODOLOGY

The papers ConductVision implements

Every metric ships with its citation. Reviewers see the same names you already cite in your methods section.

BIOPHYS J · 2004

Automatic and Quantitative Measurement of Protein-Protein Colocalization in Live Cells

Costes SV, Daelemans D, Cho EH, Dobbin Z, Pavlakis G, Lockett S.

J MICROSC · 1993

Measurement of co-localization of objects in dual-colour confocal images

Manders EMM, Verbeek FJ, Aten JA.

NAT METHODS · 2018

A guided tour into subcellular colocalization analysis in light microscopy

Bolte S, Cordelières FP.

AM J PHYSIOL CELL · 2011

A practical guide to evaluating colocalization in biological microscopy

Dunn KW, Kamocka MM, McDonald JH.

Run colocalization at cohort scale.

Per-ROI Pearson and Manders, Costes randomization, and reproducible parameter logs across thousands of fields. Ready for the methods section.

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