Formula Used
Codon adaptation index uses the geometric mean of relative adaptiveness values.
Each codon receives a weight between 0 and 1.
A preferred codon usually has a weight of 1.
CAI = exp((Σ ln(wi)) / N)
Here, wi is the codon weight for each usable codon.
N is the number of codons included in the CAI calculation.
Stop codons can be excluded because they do not encode amino acids.
Missing or zero weights use the fallback value entered in the form.
How to Use This Calculator
- Paste a DNA or RNA coding sequence into the sequence box.
- Choose the reading frame offset if leading bases exist.
- Review or replace the reference codon weight table.
- Set a minimum fallback weight for missing codons.
- Choose whether stop codons should be excluded.
- Press Calculate to show the result below the header.
- Use CSV or PDF export for records and reports.
Example Data Table
| Example |
Sequence Type |
Expected CAI Pattern |
Interpretation |
| Host optimized gene |
Mostly preferred codons |
Higher |
Better match to the selected reference profile. |
| Mixed source gene |
Preferred and rare codons |
Moderate |
May need further review before expression work. |
| Rare codon rich gene |
Many low weight codons |
Lower |
May translate less efficiently in the chosen host. |
Codon Adaptation Index Guide
What This Score Means
Codon adaptation index shows how well a coding sequence matches a chosen reference codon pattern.
It is often used when comparing genes, screening synthetic constructs, or preparing expression work.
A high value means the sequence uses codons that are frequent in the reference set.
A low value may show rare codon use, mixed origin, or poor fit for a host.
This calculator keeps the workflow transparent.
You can paste a DNA or RNA coding sequence.
You can also adjust every codon weight.
That makes the tool useful for bacteria, yeast, plants, animals, and custom studies.
Why Reference Weights Matter
CAI is not a direct expression guarantee.
It is a bias score based on relative adaptiveness weights.
Those weights should ideally come from highly expressed genes in the target organism.
The default table is only a practical starter set.
Replace it when organism specific data is available.
The calculator also reports GC percent and GC at third codon positions.
These values help explain why two genes with similar CAI scores can still behave differently.
Codon counts are shown in a detailed table.
Missing weights, stops, invalid codons, and trimmed bases are also reported.
Advanced Review Tips
Advanced users can test design changes quickly.
For example, change several codon weights and submit again.
Then compare CAI, GC3, and the codon summary.
A compact CSV file supports spreadsheet review.
The PDF export supports simple reporting.
Both exports use the current calculated result.
Use the reading frame option when a pasted sequence has leading bases.
The incomplete tail is trimmed before codons are analyzed.
Best Practice Notes
For best results, enter a clean coding region.
Remove introns, UTRs, labels, and formatting notes.
Keep the start and stop logic consistent with your project.
Ignore stop codons when you only want the coding body score.
Include warnings when sharing results.
CAI should be interpreted with codon context, mRNA structure, motifs, translation rate, and experimental goals.
This balanced view makes the number more useful.
It also prevents overconfidence.
The example table below shows how different sequences can produce different scores.
It is included for layout testing and user education.
Real projects should use a reference set from the same host and condition.
That choice improves interpretation and reduces misleading comparisons.
Always document the source of your weights.
FAQs
What is codon adaptation index?
Codon adaptation index is a score that compares codon choices in a coding sequence against a reference codon weight profile. Higher values show stronger agreement with that profile.
What value is considered high?
A value near 1 is high. Many users treat values above 0.80 as strongly adapted, but the meaning depends on the organism and reference set.
Can I paste RNA sequences?
Yes. The calculator converts U to T before analysis. It then reads the sequence as codons using the selected reading frame offset.
Should stop codons be included?
Most CAI workflows exclude stop codons because they do not encode amino acids. The checkbox lets you keep the common exclusion behavior.
Why do custom weights matter?
Different organisms prefer different codons. Custom weights help match the calculation to the target host, tissue, strain, or reference gene collection.
What happens to invalid characters?
Characters outside A, C, G, T, and U are removed. The result table reports how many characters were ignored during cleaning.
Why is GC3 reported?
GC3 shows how often the third codon position uses G or C. It helps describe codon bias beyond the CAI score alone.
Can CAI predict protein expression perfectly?
No. CAI is useful, but expression also depends on mRNA structure, promoters, motifs, translation speed, folding, host biology, and experimental conditions.