ELISA data analysis is where a good assay is either confirmed or quietly ruined. The plate reader gives you optical densities; everything after that — blank handling, curve model, interpolation, quantitation limits — decides whether your concentrations are defensible. This guide walks the full workflow in the order you should actually do it.

1. Start from raw optical density, not a pre-processed export

Keep the raw OD matrix as your single source of truth. Reader software often applies its own blank correction or curve fit silently, so re-analyzing an already-processed export double-corrects the data. Export the plain grid (rows A–H, columns 1–12) and work from that.

2. Subtract the blank correctly

Average your blank replicates and subtract that mean from every well, standards included.

Use the mean of all blanks, not a single well — one pipetting artifact should not shift the whole plate.
Blank-corrected values can legitimately go slightly negative for low samples. Do not clip them to zero; clipping biases the low end of the curve upward.
A zero standard is a background anchor, not a quantifiable point: log(0) is undefined, so it cannot sit on a logistic curve.

3. Fit the standard curve with 4PL (or 5PL when asymmetric)

ELISA standard curves are sigmoidal on a log-concentration axis, so linear or log-linear fits systematically distort both ends.

The four-parameter logistic model:

OD = D + (A - D) / (1 + (conc / C)^B)

Parameter	Meaning
A	Lower asymptote (background plateau)
B	Hill slope (steepness)
C	EC50 / inflection point
D	Upper asymptote (saturation)

Use 5PL when the curve is visibly asymmetric — it adds an asymmetry exponent and usually recovers accuracy at the top of the range. Weight the fit (1/Y or 1/Y²) when replicate variance grows with signal, which is typical for colorimetric readouts.

4. Judge the fit with more than R²

R² above 0.99 is routine for ELISA and hides real problems. Check these instead:

Back-calculated standards. Re-interpolate each standard through your own curve. Recovery should sit within 80–120% (±20% bias); 85–115% for the middle of the range.
Residual pattern. Residuals should scatter randomly. A systematic S-shape means the wrong model, not noise.
ΔOD between top and bottom standard. A dynamic range of only ~0.3 OD means the assay barely responds — no fit can rescue that.
EC50 position. If EC50 lands outside the standard range or its 95% confidence interval spans orders of magnitude, the curve is extrapolated and unreliable.

5. Interpolate samples — and respect LLOQ/ULOQ

Invert the fitted model to convert sample OD into concentration:

conc = C * ((A - D) / (OD - D) - 1)^(1 / B)

Define your quantitation limits from the curve, not from wishful thinking:

LLOQ = lowest non-zero standard that still meets accuracy and precision criteria.
ULOQ = highest standard.

Anything below LLOQ or above ULOQ is extrapolated. Report it flagged (< LLOQ, > ULOQ) rather than as a number, and dilute and re-run high samples instead of trusting the saturated plateau.

6. Apply dilution factors and normalization last

Multiply the interpolated concentration by the dilution factor after interpolation. If you normalize to total protein, propagate the error: relative SD of the ratio combines the relative SDs of analyte and protein in quadrature.

7. Run the precision checks before reporting

Replicate %CV — under 15% for samples, under 10% for standards. High %CV on a single duplicate usually means a pipetting or bubble artifact.
Outliers — test formally (e.g. Grubbs') instead of removing the point you dislike.
Missing wells — leave them missing. Substituting zero fabricates a measurement.

A reproducible checklist

Raw OD grid exported unprocessed
Mean blank subtracted from all wells
4PL/5PL fitted on log-concentration axis, weighted if needed
Standards back-calculated, recovery within ±20%
Residuals random, ΔOD adequate, EC50 inside range
Samples interpolated, out-of-range values flagged
Dilution factors and normalization applied with error propagation
Replicate %CV reported alongside every concentration

Doing it without a spreadsheet

Every step above is implemented in Labreador's ELISA module — paste or upload the reader grid, assign wells, and you get the 4PL/5PL fit, back-calculated standard recovery, method health warnings, LLOQ/ULOQ flags and %CV in one pass. Everything runs in your browser: no account, no upload, no data leaving your machine.

If you use it in a publication, please cite:

Labreador - Bioassay Analysis Platform (Version 1.6.0) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.21676846

ELISA Data Analysis: A Step-by-Step Guide (2026)