Improving PacBio Long Read Accuracy by Short Read Alignment

By Kin Fai Au, J. Underwood, Lawrence Lee, Wing Hung Wong. PLoS ONE, 2012

306 citations recorded by the source corpus.

The recent development of third generation sequencing (TGS) generates much longer reads than second generation sequencing (SGS) and thus provides a chance to solve problems that are difficult to study through SGS alone. However, higher raw read error rates are an intrinsic drawback in most TGS technologies. Here we present a computational method, LSC, to perform error correction of TGS long reads (LR) by SGS short reads (SR). Aiming to reduce the error rate in homopolymer runs in the main TGS platform, the PacBio® RS, LSC applies a homopolymer compression (HC) transformation strategy to increase the sensitivity of SR-LR alignment without scarifying alignment accuracy. We applied LSC to 100,000 PacBio long reads from human brain cerebellum RNA-seq data and 64 million single-end 75 bp reads from human brain RNA-seq data. The results show LSC can correct PacBio long reads to reduce the error rate by more than 3 folds. The improved accuracy greatly benefits many downstream analyses, such as directional gene isoform detection in RNA-seq study. Compared with another hybrid correction tool, LSC can achieve over double the sensitivity and similar specificity.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/f470264876022001b948bd08271cf537ea5c2d12

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Citations in the corpus

proovread: large-scale high-accuracy PacBio correction through iterative short read consensus (2014, methodology): “This data set was previously used to assess the performance of LSC (Au et al., 2012), although here we used a more recent version of the program (0.3.1). proovread was run with two diﬀerent parameter settings: (i) the default settings and (ii) a modiﬁed set tailored-made for transcriptomic data…”
SSPACE-LongRead: scaffolding bacterial draft genomes using long read sequence information (2014, methodology): “To date a few algorithms have been released that are capable of upgrading PacBio CLR data with high accuracy data from CCS or short read NGS data, among which PacBioToCA [9] and LSC [10].”
A survey of best practices for RNA-seq data analysis (2016, background): “Nevertheless, long-read sequencing has its own set of limitations, such as a still high error rate that limits de novo transcript identifications and forces the technology to leverage the reference genome [188].”
Nanopore sequencing technology, bioinformatics and applications (2021, methodology): “4, middle right, and Table 1): ‘self-correction’ uses graph-based approaches to produce consensus sequences among different molecules from the same origins (for example, Canu 88 and LoRMA 89 ) in contrast to 2D and 1D 2 reads generated from the same molecules, and ‘hybrid correction’ uses high-accur”
Contiguous and accurate de novo assembly of metazoan genomes with modest long read coverage (2015, unknown): “The hybrid error corrector LSC (27) was not tested in detail due to the fundamental similarity of its assembly approach to that of ectools and Lordec, though preliminary data (not shown) did not indicate superior read correction by LSC versus these other approaches.”
PacBio Sequencing and Its Applications (2015, methodology): “have developed the tool LSC for the correction of raw PacBio reads by SGS short reads [57].”