Rapid Real time Squiggle-level Classification for Read-Until Using RawMap
- Published on: June 19 2020
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Read-Until enables Oxford Nanopore (ONT) sequencers to selectively sequence target reads of interest in real-time. Read-Until achieves rapid target enrichment for applications such as microbiome abundance estimation where the metagenomic sample has a significant fraction of non-target reads (>99% can be human reads). However, Read-Until requires a fast and accurate classifier that analyzes a short prefix of a read and determines whether the read belongs to one of the target species. The conventional read-until pipeline using a sequence of basecaller (e.g. Guppy), aligner (e.g, Minimap2), and classifier (e.g, Centrifuge) cannot classify 10% of the reads. In figure 1, we show that our proposed pipeline yields significant savings in terms of basepairs saved from forward translocation, cost and speedup on a 99:1 human-zymo DNA mix where the average read length is 20Kbp. Here, cost savings refers to increased lifetime of the flowcell and speedup refers to improvement in end-to-end sequencing time.
