Improving PacBio long read accuracy by short read alignment

• Published in: PloS one Vol. 7; no. 10; p. e46679
• Main Authors: Au, Kin Fai, Underwood, Jason G, Lee, Lawrence, Wong, Wing Hung
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 04.10.2012; Public Library of Science (PLoS)
• Subjects: Accuracy; Alignment; Analysis; Bioinformatics; Biology; Brain; Cerebellum; Compression; Computational Biology - methods; Computational neuroscience; Error correction; Error correction & detection; Genetic transformation; Genomes; Quality control; Reproducibility of Results; Ribonucleic acid; RNA; Sensitivity; Sequence Analysis, DNA; Sequence Analysis, RNA; Software; Transformation; United States > US; California
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0046679

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.