Scalable long read self-correction and assembly polishing with multiple sequence alignment

Abstract

Third-generation sequencing technologies allow to sequence long reads of tens of kbp, that are expected to solve various problems. However, they display high error rates, currently capped around 10%. Self-correction is thus regularly used in long reads analysis projects. We introduce CONSENT, a new self-correction method that relies both on multiple sequence alignment and local de Bruijn graphs. To ensure scalability, multiple sequence alignment computation benefits from a new and efficient segmentation strategy, allowing a massive speedup. CONSENT compares well to the state-of-the-art, and performs better on real Oxford Nanopore data. Specifically, CONSENT is the only method that efficiently scales to ultra-long reads, and allows to process a full human dataset, containing reads reaching up to 1.5 Mbp, in 10 days. Moreover, our experiments show that error correction with CONSENT improves the quality of Flye assemblies. Additionally, CONSENT implements a polishing feature, allowing to correct raw assemblies. Our experiments show that CONSENT is 2-38x times faster than other polishing tools, while providing comparable results. Furthermore, we show that, on a human dataset, assembling the raw data and polishing the assembly is less resource consuming than correcting and then assembling the reads, while providing better results. CONSENT is available at https://github.com/morispi/CONSENT.

DeepConsensus: Gap-Aware Sequence Transformers for Sequence Correction

“…The correction of errors in sequencing data is fundamental to both the generation of initial data from a sequencer and to downstream analyses which assemble, map, and analyze genomes [28][29][30] . We introduce a transformer-based consensus generation method, reducing errors in PacBio HiFi reads by 42% and increasing yield of 99.9% accurate reads by 27%.…”

High molecular weight DNA extraction strategies for long-read sequencing of complex metagenomes

“…CC-BY-ND 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted March 3, 2021. ; https://doi.org/10.1101/2021.03.03.433801 doi: bioRxiv preprint 19 Vaser et al 2017;Walker et al 2014;Morisse et al 2021), will lead to new insights in metagenomics especially with complete circular MAGs.…”

phasebook: haplotype-aware de novo assembly of diploid genomes from long reads

“…For small genomes or specific genomic regions such as MHCs, we make use of a method for self-correction of long reads in each read group. This method combines a multiple sequence alignment (MSA) strategy with local de Bruijn graphs and is implemented in CONSENT [ 34 ]. When dealing with large genomes (e.g., Chr6), to increase efficiency, we use the MSA-based error correction modules built in MECAT2 [ 35 ] and NECAT [ 36 ] for PacBio CLR and Nanopore reads, respectively.…”