Accuracy

Nanopore sequencing provides direct electronic analysis of the target molecule, rather than sequencing a synthetic copy or using surrogate markers such as fluorescence. Basecalling algorithms are then used to provide an interpretable output of the sequencing reads. Nanopore basecalling algorithms are continuously improved to enhance accuracy over time, also allowing new methods to be applied to previously sequenced raw data. 

Direct sequencing avoids sources of bias such as PCR and gives native information about the target molecule. We define raw read accuracy as the accuracy achieved when reading a single DNA or RNA fragment/molecule once. Applications for which raw read sequencing is relevant include those where time-to-result maybe be critical, but at this time most applications are more likely to focus on variant calling, consensus accuracy or other metrics. Improvements in raw read accuracy can drive improvements in other accuracy metrics.

Consensus generation can also be applied to specific regions of interest, by combining multiple exact copies of a single original fragment or molecule into a single high-quality sequence. These exact copies could be sequenced together in a single read, for example generated by circular or linear amplification, or could be associated by use of a unique identifier (UMI). Through combining multiple copies together, a higher confidence in accuracy is achieved.

Applications where single molecule consensus could be particularly useful include liquid biopsy low-frequency variant detection, or 16S sequencing.

Single nucleotide variants (SNVs), small indels and structural variants (SVs) are critical for our understanding of how genomic changes drive phenotypes. The ability of nanopore technology to sequence any length of nucleic acid molecule allows for unprecedented resolution of complex structural variants, as well as identification and haplotype phasing of single nucleotide alterations.

The ability to accurately call variants is often expressed as precision and recall values, generated from reads covering the position of interest multiple times. Precision is the proportion of calls in the call set that are correct, whereas recall is the percentage of variants present in the genome that are found in the call set.

The latest precision, recall and F1 (a harmonic mean of precision and recall) for nanopore chemistries can be found below, along with a recommended tool chain to achieve similar metrics.

Oxford Nanopore Technologies Open Datasets: SV, SNP.

The four ‘canonical’ bases (A, C, G and T in DNA and A, C, G and U in RNA) can be biologically modified by the presence of additional chemical group, such as methylation. These modifications can significantly alter gene expression and are implicated in a range of diseases including cancer. Scientists are only just beginning to scratch the surface of how newly-recognised epigenetic changes impact function, for example, RNA is known to possess over 170 distinct modifications.

Oxford Nanopore’s technology can sequence the DNA or RNA molecules directly, enabling direct, real-time detection of 5mC, 5hmC, 6mA.

This allows for detection of these base modifications with no additional experiments or sample preparation steps required, and modification information is accessible through onboard software. In contrast, traditional technologies can require a separate process called bisulphite sequencing, which uses aggressive sample treatment and has a number of limitations.

Recent publications have shown excellent correlation between nanopore modification detection and existing techniques, as well as further modification sites detected that had previously been missed by alternative approaches.

Find out more about our methylation analysis benchmarking.