Nanopore sequencing accuracy

For many years Oxford Nanopore has continuously iterated our technology to improve its performance. We continue to improve the nanopore sensing system, through updates to analytical methods and new chemistries. This page guides you on what to expect from the nanopore sequencing system, and which tools to choose to achieve these results.

What is sequencing accuracy?

Accuracy is a generic term that might refer to different aspects of DNA and RNA sequencing performance. Typically, it refers to the accuracy at a single read level or at the consensus level, combining the information from multiple reads of a DNA/RNA region into a single high-quality sequence. Depending on the application, other relevant factors to consider are the proportion of the genome covered and the ability to detect epigenetic modifications. Usually, genomic research focuses either on resequencing and mapping to a reference genome or reconstructing unknown genomes through de novo assembly. For mapping-based projects, changes compared with the reference sequences are used for inference, hence variant calling becomes the main focus. For de novo assembly, quality is estimated by the accuracy of the reconstructed sequence and other metrics such as N50.

Variant calling accuracy

Variant calling identifies differences from a reference sequence and is crucial in understanding how genotypes drive phenotypes. Nanopore technology can sequence any length of DNA and RNA molecule, offering unprecedented resolution of complex structural variants and efficient haplotype phasing of variants.

Measuring the accuracy of variant calling is critical to ensure that the genetic variants identified are biological differences and not artefacts. Accuracy is commonly measured with the so called F1 score, the harmonic mean of precision (proportion of called variants that are actually variants) and sensitivity or recall (proportion of all variants that are correctly called). This metric is especially useful when you want to balance the trade-off between identifying as many variants as possible (high sensitivity) and ensuring the variants identified are truly variants (high precision).

Learn more about accuracy measures.

Read more about structural variation and small variant calling & phasing.

Nanopore sequencing achieves:

Figure 1. Accuracy data obtained with Ligation Sequencing Kit V14 and PromethION R10.4.1 Flow Cell, measured as F1 score for variant calling, using nanopore sequencing data for the human genome (HG002 cell lines) at several read depths (Kit V14 400 bps 5kHz). Variant calling was performed with Clair3 variant caller, and variants were compared against the Genome In A Bottle consortium’s HG002 truth-set (v4.2.1). SNVs and indels are represented with solid colours, while indels in coding regions (CDS) are displayed with white boxes. A) F1 score for basecalling models of super accuracy (SUP, v4.2.0) using Dorado v0.2.5 B) F1 score for basecalling models of high accuracy (HAC, v4.2.0) using Dorado v0.2.5.

Our SNP calls produced with [nanopore sequencing] … were comparable to state-of-the-art short-read-based methods

Kolmogorov et al. Nat. Methods (2023)

[With nanopore Q20 chemistry] It is now realistic to use long read sequencers to systematically analyze a wider range of cancerous mutations

Sakamoto et al. Nat. Commun. (2022)

Base modification accuracy

The four DNA bases (A, C, G, T) and RNA bases (A, C, G, U) can undergo biological modifications like methylation, impacting gene expression and contributing to diseases such as cancer. Oxford Nanopore’s technology allows for direct, real-time sequencing and detection of these modifications for both DNA and RNA (e.g. 5mC, 5hmC, 6mA, 4mC for DNA, and m6A for RNA) without additional experiments or preparation, unlike legacy methods, such as bisulphite sequencing, that have several limitations.

Read more about direct DNA and RNA base modifications detection

Our methylation calls [with nanopore sequencing] were highly concordant with the standard bisulfite sequencing, but in addition had haplotype-specific resolution

Kolmogorov et al. Nat. Methods (2023)

Figure 2. Oxford Nanopore 5mC data comparison to synthetic (A) and bisulfite sequencing data (B). Basecalling of 5mC on synthetic strands with known composition is extremely accurate with precision, recall, and F1 score all above 99%. Oxford Nanopore data for the human sample HG002 shows much higher confidence CpGs (>90%) at a much lower depth than bisufite whole-genome sequencing (WGS). All data reported in this figure was generated with Ligation Sequencing Kit V14 and PromethION R10.4.1 Flow Cell with 400 bps speed, 4 kHz using SUP basecalling models.

Assembly accuracy

Assembly accuracy refers to the degree to which a reconstructed sequence of DNA or RNA matches the true biological sequence from which it was derived. This involves building a consensus sequence from multiple DNA/RNA reads, enhancing accuracy and creating a reliable sequence for further analysis.

Find out more about assembly & whole-genome sequencing.

Nanopore sequencing achieves:

Flow cell Library preparation kit Assembly accuracy Sequencing & basecalling parameters Analysis tools Sample
PromethION R10.4.1 Ligation Sequencing Kit V14 Ultra-long Sequencing Kit V14 Telomere-to-telomere (T2T): Q42* 18 full chromosome haplotype- resolved, N50 >135 Mb 400 bps, 5 kHz, simplex SUP, duplex Assembly with Verkko, phasing with Gfase Human HG002
MinION R10.4.1 Ligation Sequencing Kit V14 Q50 at 10–20x 400 bps, 4 kHz, simplex SUP Assembly with Flye Zymo mock community (bacterial)

*Generated by combining approx. 40x duplex, 40x ultra-long and 40x Pore-C

Covering all of the genome

To create an accurate picture of the genome, it is important for a sequencing technology to reach all parts of it, even the parts which are difficult to map. Genomes are littered with repetitive and low-complexity regions, which are difficult to sequence and align using legacy technologies. For example, it is estimated that short-read technology reaches only 92% of the human genome, leaving 8% that contains many disease-relevant genes excluded from the dataset.

Nanopore technology has been shown to reduce these ‘dark’ areas of the genome by 81%, shedding light on parts of the genome not sequenced by any other technology (Ebbert et al., 2019), and giving a more complete picture. The extensive genome mapping capabilities of nanopore data manage to achieve 99.49% genome coverage (Uddin et al., 2024). Ultra-long nanopore sequencing reads were central to completing the human genome, resolving repetitive regions that were unattainable with other technologies (Nurk et al., 2022).

[Nanopore] sequencing allowed us to unravel the only two unsolved cases … for which different genetic testing approaches had been sequentially performed for > 10 years unsuccessfully

Damián et al. Hum. Genomics (2023)

Raw read and single molecule accuracy

Nanopore sequencing uses direct electronic analysis of native DNA and RNA molecules to generate raw reads, eliminating PCR bias. Basecalling algorithms based on machine learning have been improving with time, providing more and more accurate reads. Raw read accuracy refers to the accuracy achieved when reading a single DNA or RNA strand once. Most applications focus on variant calling, consensus accuracy, or other metrics, where the information from several reads is combined. These can be improved by increased raw read accuracy but can also be enhanced in other ways (e.g. increased genome coverage).

Duplex sequencing suits applications in which single-molecule sequencing is relevant; by reading both DNA strands, the reads generated achieve a high-quality single molecule accuracy. Our latest Q20+ chemistry enables the generation of duplex reads: the second strand can follow the first through the same nanopore, producing information from two orthogonal signals, merged into one consensus sequence. Single molecule accuracy of duplex is ~Q30 or higher. A specific basecaller for nanopore duplex reads is available.

Nanopore sequencing achieves:

Flow cell Library preparation kit Sequencing & basecalling parameters Sample Accuracy Output
PromethION R10.4.1 Ligation Sequencing Kit V14 400 bps, 5 kHz, HAC basecalling Human HG002 99.0% (Q20) ●●●
PromethION R10.4.1 Ligation Sequencing Kit V14 400 bps, 5 kHz, SUP basecalling Human HG002 99.5% (Q23) ●●●
PromethION R10.4.1 Ligation Sequencing Kit V14 400 bps, 5 kHz, Duplex basecalling Human HG002 >99.9% (Q30)

Tuning accuracy for your experimental need

Optimise accuracy according to your requirements by selecting simplex or duplex reads and the most suitable basecalling model. Simplex reads achieve Q20 accuracy and are generated by reading a single DNA/RNA strand through a nanopore, and accuracy fine-tuned with the following basecalling models.

  • Fast basecalling: fastest, least computationally intense. Highest compatibility with real-time basecalling on device

  • High accuracy basecalling (HAC): highly accurate, intermediate speed and computational requirement. Good compatibility with real-time basecalling device

  • Super accuracy basecalling (SUP): the most accurate and computationally intense

Duplex reads achieve Q30 accuracy by combining the information from both DNA strands. A specific basecaller for nanopore duplex reads is available, with computational requirement similar to the SUP basecalling model.

Explore simplex sequencing

Available datasets

Oxford Nanopore Technologies provides open access to a range of nanopore sequencing datasets through its initiative hosted on Amazon Web Services (AWS), called ‘ont-open-data’. This initiative allows researchers worldwide to explore and utilise extensive sequencing data to enhance their genomic studies. For example, the dataset for the human genome sample GM24385 (HG002) is one of the available resources, which has been utilised in numerous research applications, reflecting Oxford Nanopore's commitment to supporting the scientific community by providing freely accessible, high-quality data.

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