Advanced Genome Size Calculator

Analyze sequencing depth, k-mer peaks, and fluorescence standards. Convert bases into Mb, Gb, and picograms. Get fast comparisons, exports, graphs, and interpretation notes instantly.

Genome size calculator form

Choose one estimation method, enter your measurements, and submit. The result will appear above this form.

Pick the method matching your available experimental data.
Used to report total nuclear DNA content from the haploid estimate.
Optional. Used to compare assembly span with the estimated haploid genome size.

Coverage-based inputs

Use total single reads or paired read units, depending on the setting below.
Average usable bases per read after trimming.
Average depth expected across the haploid genome.
Percent of bases treated as effective genome-derived sequence.
Choose how your count should be converted into total sequenced bases.

K-mer peak inputs

Use the histogram total after filtering obvious error k-mers.
Use the dominant genomic peak, not the low-depth error shoulder.
Adjust if only a portion of total k-mers is suitable for estimation.

Flow cytometry ratio inputs

Use the corrected mean or peak fluorescence for the unknown sample.
Use a matched reference standard measured under the same conditions.
Enter the known genome size for the reference standard.
The calculator converts the reference into base pairs internally.

Example data table

These examples show how different biological workflows can produce a genome size estimate.

Method Example inputs Estimated haploid size Total DNA at ploidy 2 Interpretation
Coverage-based 50,000,000 paired reads, 150 bp, 30×, 90% usable 450.00 Mb 900.00 Mb Useful when total bases and expected depth are known.
K-mer peak 120,000,000,000 valid k-mers, peak depth 40, 95% usable 2,850.00 Mb 5,700.00 Mb Helpful for short-read survey data and genome profiling.
Flow cytometry ratio Sample 240, reference 200, standard 3,200 Mb 3,840.00 Mb 7,680.00 Mb Best when fluorescence ratios are measured against a standard.

Formula used

1) Coverage-based estimate

Genome size (bp) = Effective sequenced bases / Coverage depth

Effective sequenced bases = Read count × Read length × Layout factor × Usable fraction.

2) K-mer peak estimate

Genome size (bp) = Effective k-mers / Peak depth

Effective k-mers = Total valid k-mers × Usable fraction.

3) Flow cytometry ratio estimate

Genome size (bp) = (Sample fluorescence / Reference fluorescence) × Reference genome size

This scales the known reference size by the observed fluorescence ratio.

Unit conversion

1 Mb = 1,000,000 bp, 1 Gb = 1,000,000,000 bp, and 1 pg ≈ 978 Mb.

How to use this calculator

  1. Select the estimation method matching your experiment.
  2. Enter ploidy so total nuclear DNA content can be reported correctly.
  3. Fill in the method-specific measurements, such as coverage, k-mer peak, or fluorescence ratio values.
  4. Optionally enter assembly span in Mb to compare assembly completeness with the estimated haploid genome size.
  5. Click Calculate Genome Size to display the result above the form.
  6. Review the summary, detailed method table, and sensitivity graph.
  7. Use the CSV or PDF buttons to save the calculation report.

FAQs

1) What does genome size mean?

Genome size is the amount of DNA in one haploid set of chromosomes. It is usually reported in base pairs, megabases, gigabases, or picograms.

2) Which method should I choose?

Choose coverage-based when sequencing yield and expected depth are known. Choose k-mer when you have histogram totals and a clear peak. Choose flow cytometry when fluorescence is measured against a reference standard.

3) Why is ploidy entered separately?

Most genome size discussions use the haploid genome. Ploidy helps convert that estimate into total nuclear DNA content for diploid, triploid, or polyploid cells.

4) What can make a coverage estimate inaccurate?

Bias can come from contamination, organelle reads, uneven depth, duplicated reads, poor trimming, or a wrong assumption about the fraction of bases that truly represent the target genome.

5) What can make a k-mer estimate inaccurate?

Using the wrong peak is common. Error k-mers, repeats, heterozygosity, contamination, and incomplete histogram filtering can all shift the final estimate.

6) Why compare assembly span with the estimate?

Assembly span helps you judge completeness. A much smaller assembly may indicate missing repeats, collapsed regions, contamination filtering, or conservative assembly settings.

7) What does the graph show?

The graph shows how the estimated genome size changes if your key assumption shifts. That key assumption is coverage depth, k-mer peak depth, or fluorescence ratio, depending on the chosen method.

8) Can I report results in picograms?

Yes. The calculator automatically converts the estimate into picograms using the common approximation that 1 pg of DNA equals about 978 megabases.

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Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.