Calculating & Analyzing ELISA data
This page details the recommended guidelines for calculating results from ELISA data and statical assay validation.
Depending on the type of ELISA used (qualitative, semi-quantitative or quantitative) data output will vary. Therefore you should choose the specific ELISA you want to use based on the data that you want to analyse.
- ELISA assay reliability hinges on accurate standard curves and consistent protocols.
- Controls and Coefficient of Variation ensure precision; Spike Recovery tests sample matrix compatibility.
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Calculating Results from ELISA Data
Data is presented as a plot of optical density (OD) vs the log concentration of sample. Standards with known concentrations are used to generate a standard curve from which the concentration of an unknown analyte can be determined.
When performing an ELISA assays it is good practice to run samples in duplicate or triplicate to ensure statistical validation of results.
Include positive and negative controls when setting up your ELISA plates.
- Negative controls: Samples with no presence of your analyte
- Positive controls: Samples with a known presence or quantity of your analyte
Preparing an ELISA Standard Curve
Once you have completed your ELISA protocol and analysed your samples & standards using a plate reader, you can plot your standard curve. In order to plot your standard curve for your analyte you plot the mean absorbance (Y axis) versus the known protein concentration of your standards (X axis). Use a computer to draw a best fit curve to plot your data.
Sandwich ELISA Standard Curve
General standard curve for a sandwich CD8A ELISA. OD450 correlates with the amount of analyte (CD8A) present in the sample.
Competitive ELISA Standard Curve
General standard curve for a competitive Prepronociceptin ELISA. Reduction in OD450 value correlates with the amount of preponociceptin in the sample.
Related ELISA Resources
Calculating the Absorbance
Calculate the average absorbance from duplicate/triplicate standards and samples. These should be within 20% of the mean.
Create a standard curve as described below
Plot the mean absorbance (y axis) against the protein concentration (x axis) using excel or a similar suitable computer programme for standard samples.
Draw a best fit curve through the points on the graph.
From the standard curve graph extend a horizontal line from the absorbance plotted on the y axis to the standard curve.
Upon reaching the standard curve drop a vertical line down to read off the protein concentration.
To obtain an accurate result, these samples should be diluted before proceeding with the ELISA protocol. For these samples, the concentration obtained from the standard curve when analysing the results must be multiplied by the dilution factor
Coefficient of Variation
The coefficient of variation helps identify any inconsistences and inaccuracies in the results. It is expressed as a percentage of variance to the mean. The larger the variance the greater the inconsistency and error. The coefficient variation (CV) is the ratio of the standard deviation σ to the mean µ:
A High CV can be attributed to some or all of the following:
- Sample contamination with bacteria/fungi or other reagents
- Pipetting inaccuracies
- Drying out of wells – plates should be covered during all incubation steps
- Temperature variation- plates should be incubated at a stable temperature away from drafts
At Assay Genie each kit we produce is analysed to determine the sensitivity, range and inter/ intra assay CV(%). This will ensure you know the full capabilities of our ELISA Kits including variability in advance of purchasing.
Spike-recovery determines if any components in the sample interfere in antibody-antigen binding. The sample matrix is spiked with a known concentration of recombinant target protein. The ELISA is performed and the concentrations of protein determined from the standard curve. Recovery is typically presented as a percentage. Anything less than 80% generally means that components in the matrix are interfering in the ELISA and a different kit should be chosen At ELISA genie we understand the need to show the accuracy of our ELISA kits but we also know how important it is to see if anything in the sample matrix interferes with antibody-antigen binding, a key step in ELISA. That is why we painstakingly do linearity and spike recovery analysis on every ELISA kit batch we produce.
Written by Sean Mac Fhearraigh
Seán Mac Fhearraigh PhD is a co-founder of Assay Genie. Seán carried out his undergraduate degree in Genetics at Trinity College Dublin, followed by a PhD at University College Dublin. He carried out a post-doc at the Department of Genetics, University of Cambridge. Seán is now Chief Technical Officer at Assay Genie.