Conventional targeted sequencing methods eliminate many of the benefits of nanopore sequencing, such as the ability to accurately detect structural variants or epigenetic modifications. The ReadUntil method allows nanopore devices to selectively eject reads from pores in real time, which could enable purely computational targeted sequencing. However, this requires rapid identification of on-target reads while most mapping methods require computationally intensive basecalling. We present UNCALLED (https://github.com/skovaka/UNCALLED), an open source mapper that rapidly matches streaming of nanopore current signals to a reference sequence. UNCALLED probabilistically considers k-mers that could be represented by the signal and then prunes the candidates based on the reference encoded within a Ferragina–Manzini index. We used UNCALLED to deplete sequencing of known bacterial genomes within a metagenomics community, enriching the remaining species 4.46-fold. UNCALLED also enriched 148 human genes associated with hereditary cancers to 29.6× coverage using one MinION flowcell, enabling accurate detection of single-nucleotide polymorphisms, insertions and deletions, structural variants and methylation in these genes.

传统的靶向测序方法消除了纳米孔测序的许多优点，例如准确检测结构变异或表观遗传修饰的能力。ReadUntil 方法允许纳米孔设备实时选择性地从孔中弹出读数，这可以实现纯粹的计算靶向测序。然而，这需要快速识别目标读数，而大多数作图方法需要计算密集型碱基识别。我们提出了 UNCALLED (https://github.com/skovaka/UNCALLED)，这是一种开源映射器，可以将纳米孔电流信号流与参考序列快速匹配。UNCALLED 概率性地考虑可由信号表示的k聚体，然后根据 Ferragina-Manzini 索引中编码的参考修剪候选者。我们使用 UNCALLED 来消除宏基因组群落中已知细菌基因组的测序，使剩余物种丰富了 4.46 倍。UNCALLED 还使用一个 MinION 流通池将 148 个与遗传性癌症相关的人类基因富集至 29.6 倍覆盖范围，从而能够准确检测这些基因中的单核苷酸多态性、插入和缺失、结构变异和甲基化。