Analyze ELISA assay data with 4-parameter logistic curve fitting and calculate sample concentrations from optical density values.
ELISA (Enzyme-Linked Immunosorbent Assay) data analysis involves fitting a standard curve to known concentrations and calculating unknown sample concentrations from optical density measurements. This tool uses 4-parameter logistic regression for accurate curve fitting.
Quick guide to analyze your ELISA data:
This tool is useful when you need to:
Sample ELISA data format:
Standards (concentration,OD): 1000,2.85 500,2.42 250,1.89 125,1.32 Samples (name,OD): Sample1,1.75 Sample2,1.23Supports comma or tab separated values.
Analysis results include:
R² = 0.9985 Sample1: 387.2 ng/mL (CV: 2.3%) Sample2: 234.7 ng/mL (CV: 1.8%) Standard Curve: 4PL fit Background correctedIncludes curve statistics and concentration calculations.
Q: What curve fitting method is used?
A: 4-parameter logistic (4PL) regression for optimal ELISA curve fitting.
Q: How are outliers detected?
A: Using residual analysis with 2.5x standard deviation threshold.
Q: Can I analyze multiple plates?
A: Yes, just include all standards and samples in the input.