Experimental Design

Assay Designer

Design optimized experimental assays with protocol templates, control recommendations, and sample size calculations.

Assay Type

Duration

4-6 hours

Cost

$5-15

Throughput

High

Complexity

Medium

Sample Size Calculator

Effect Size (Cohen's d)0.8

SmallMediumLarge

Number of Groups2

Recommended Sample Size25

Per group: 25

Total: 50

Power: 80%

α: 0.05

Robust sample size. Ensure practical feasibility.

ELISA

Enzyme-Linked Immunosorbent Assay for protein quantification

QuantitativeImmunoassay

Applications

Protein quantification

Antibody detection

Cytokine profiling

Biomarker validation

Key Reagents

Capture Antibody

In coating buffer (carbonate pH 9.6)

1-10 μg/mL

Blocking Buffer

BSA or milk in PBS

1-5%

Detection Antibody

Biotinylated or HRP-conjugated

0.1-2 μg/mL

Streptavidin-HRP

If using biotinylated detection

1:1000-1:5000

TMB Substrate

Protect from light

100 μL/well

Stop Solution

2N H2SO4

50-100 μL/well

Plain-Language Summary

Plain-language summary of the suggested ELISA design.

What this assay is for

ELISA is a immunoassay technique: Enzyme-Linked Immunosorbent Assay for protein quantification.
It typically takes 4-6 hours, is medium-complexity to run, and costs around $5-15 per sample.

How many samples you likely need

About 25 per group (50 in total) to have a fair chance of detecting a large effect.
This aims for 80% statistical power — the chance of catching a real effect if one exists — using the standard 0.05 cutoff for calling a result significant.
Robust sample size. Ensure practical feasibility.

Don't forget the controls

Recombinant Standard (positive control), recommended: Validate assay sensitivity and generate standard curve
Blank Wells (negative control), recommended: Measure background signal
Untreated Sample (vehicle control): Baseline measurement for treatment comparisons
Spike-in Control (internal control): Assess matrix effects and recovery

The sample-size figure is a planning estimate from standard power-analysis formulas — it assumes a simple comparison and an expected effect size you chose. A statistician should confirm the design for a study that matters.

Peptide Database

Assay Designer

ELISA

Plain-Language Summary