Calculator
Formula used
For each sequence, the GC fraction is computed from nucleotide counts:
If melting temperature is enabled, short oligos use Tm = 2(A+T) + 4(G+C). Longer sequences use a simple length-adjusted approximation for quick screening.
How to use this calculator
- Paste sequences in FASTA format or one per line.
- Optionally upload a text/FASTA file to append inputs.
- Select how ambiguous symbols should affect the denominator.
- Click Calculate to show results above the form.
- Use Download CSV or Download PDF for reports.
Example data table
| Sample | Sequence | Expected GC% | Notes |
|---|---|---|---|
| Oligo_A | ACGTTGCA | 50.0% | Balanced bases; short oligo. |
| GenomeChunk_B | GGGCCCAAATTT | 50.0% | Equal GC and AT counts. |
| Ambiguous_C | GGCCNNAT-- | 66.7%* | *Excluding N and gaps from denominator. |
1) What GC content measures
GC content is the fraction of guanine and cytosine bases in a nucleotide sequence. Because G–C pairs form three hydrogen bonds, GC-rich regions generally show higher stability than AT-rich regions. This calculator reports GC% per sequence and also a weighted GC% across all inputs.
2) Typical ranges in real datasets
Whole-genome GC varies widely across organisms. Many bacterial genomes fall roughly between 25% and 75% GC, while vertebrate genomes often sit near the low-to-mid 40% range. Viral genomes can be very compact and biased, making GC% a fast screening feature during classification and quality checks.
3) Why GC affects temperature behavior
Higher GC often increases the melting temperature of short oligos and can shift annealing conditions in amplification workflows. The optional Tm output uses the Wallace rule for short sequences and a simple length-adjusted approximation for longer segments. Use it for quick comparisons, not final assay design.
4) Interpreting ambiguous symbols
Many sequences include N, gaps, or IUPAC ambiguity codes from assemblies or alignments. Reporting standards differ: some labs exclude ambiguous symbols from the denominator, while others include them to reflect uncertainty in the observed length. The denominator toggle makes the reporting choice explicit.
5) Batch analysis for projects
For multi-sample studies, GC% helps detect contamination, primer bias, or systematic trimming artifacts. A sudden shift in GC distribution across runs can indicate adapter carryover or filtering issues. The downloadable CSV provides a compact format for plotting GC% histograms in downstream tools.
6) Physics-style data handling
In measurement terms, GC% behaves like a derived ratio with denominator sensitivity. When ambiguous bases are excluded, you are measuring composition of confident calls only. When included, you measure composition relative to total reported length. Both are valid, but they represent different observables.
7) Reporting recommendations
For publications and lab notes, record the denominator choice and whether U was mapped to T. If sequences come from alignments, note whether gaps were present and how they were treated. This calculator surfaces those counts so the reported GC% is reproducible across pipelines and teams.
8) Using results in models
GC% can serve as a feature in clustering and classification, especially when paired with k-mer frequencies or length statistics. For physical models of hybridization, GC% is a coarse proxy for stability; detailed thermodynamic models require nearest-neighbor parameters, salt corrections, and strand concentration inputs.
FAQs
1) Can I paste multiple FASTA records at once?
Yes. Paste any number of FASTA records with lines starting with “>”. Each record is computed separately, and a weighted GC% summary is shown across all sequences.
2) What happens to lowercase letters?
If case-insensitive parsing is enabled, the calculator converts input to uppercase before counting. If disabled, lowercase characters are treated as “other” and will be listed under ambiguous counts.
3) How are N and gaps treated?
N, gaps, and other letters are tracked as ambiguous. You can choose whether ambiguous symbols contribute to the GC% denominator. This choice is shown in the results note.
4) Does the calculator work for RNA sequences?
Yes. Enable “Treat U as T” to normalize uracil to thymine for counting. This keeps GC% comparable between DNA-style and RNA-style sequence representations.
5) Is melting temperature output accurate?
It is a quick estimate. Short sequences use the Wallace rule, while longer ones use a simple approximation. For assay design, use a dedicated thermodynamics tool with salt and concentration inputs.
6) Why is weighted GC% different from averaging GC% values?
Weighted GC% sums counts across sequences, so longer sequences influence the result more than short sequences. A simple average treats every sequence equally, regardless of length.
7) How do I export results?
After calculation, use the Download CSV or Download PDF buttons above the results table. Exports are generated from the displayed table, matching your current denominator and precision settings.