Genome Calculator

Coverage and depth

Work out mean coverage from a number of reads or from an output in Gbp, or how many reads you need for a target coverage. The table shows how much of the genome reaches each depth threshold.

Reads → coverage Gbp → coverage Coverage → reads

Organism or target Genome / target size

Read length (bp) Layout

Clusters (millions)For PE = number of read pairs Reads lost (%)Duplicates, filtering, trimming

Custom threshold (×)Added to the threshold table

Mean coverage

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Genome covered at each depth threshold

Threshold	% genome	Bar

Thresholds use the Poisson (Lander-Waterman) model, which assumes reads are spread evenly. Real data is more dispersed (GC bias, repeats, capture efficiency), so percentages at high thresholds are optimistic.

Samples per run

Pick a platform, instrument and flow cell, then work out how many samples fit in a run or how many flow cells or lanes your samples need. PhiX, pool imbalance and, if you enter a genome, coverage per sample are taken into account.

How many samples fit? How many flow cells do I need?

Platform Instrument

Flow cell Read setup

Calculate per Number of flow cells

Reference application Required per sample

For PE, 1 cluster = 1 read pair

PhiX / spike-in (%)Share of the run not assigned to samples Pool imbalance (%)Headroom so the least represented sample still reaches the target

Genome or target (optional, for coverage) Genome / target size

Samples per run

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Reads per application

Recommended sequencing depth for the most common applications. These are starting points: the depth you actually need depends on your experimental design. Press Use to send a value to the Samples per run calculator.

Application	Typical read setup	Clusters / sample	Notes

Indicative values based on common recommendations (Illumina, ENCODE, 10x Genomics). For PE, 1 cluster = 1 read pair.

Million reads ↔ Gbp output

Converts both ways: edit the reads to get Gbp, or edit Gbp to get the reads.

Read length (bp) Layout

Clusters (millions)For PE = number of read pairs Output (Gbp)

Output

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Gbp = clusters (M) × read length × (2 if PE) ÷ 1000

Nucleotide counter

Paste one or more sequences (FASTA works too) to get the count of each base and its share of the total.

Sequence

Total length

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Base	Count	%

Total bases in an experiment

Number of reads × read length × number of samples.

Reads per sample

Read length (bp)

Number of samples LayoutWith PE the reads entered are read pairs

Total bases

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bases = reads × read length × samples × (2 if PE)

GC% and melting temperature

For primers, probes and adapters: length, GC content, Tm with three methods and reverse complement.

Sequence (5′ → 3′)

Na⁺ (mM) Oligo (nM)

Example: M13 forward (−20) primer.

Tm (nearest-neighbor)

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Reverse complement

Complement (3′ → 5′)

Nearest-neighbor: SantaLucia (1998) parameters with Na⁺ correction. Wallace: 2·(A+T) + 4·(G+C), suited to oligos under 14 nt. Salt-adjusted formula: 81.5 + 16.6·log₁₀[Na⁺] + 0.41·GC% − 675/N.

Disk storage estimate

Approximate size of the files produced, per sample and for the whole project.

Number of samples Clusters per sample (millions)

Read length (bp) Layout

Files to include Uncompressed FASTQ FASTQ.gz BAM CRAM VCF.gz

VCF type

Estimation factors (bytes per base)

FASTQ FASTQ.gz BAM CRAM

Project total

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File	Per sample	Project

Indicative estimates: actual compression depends on the instrument, quality-score binning and aligner. Adjust the factors if you know your lab's values.

Unit converter

Quick conversions between base units, between clusters and reads, and between output and coverage.

Bases

Clusters ↔ reads

Clusters (millions) Layout

Output ↔ coverage

Output (Gbp) Genome size