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Background  Targeted resequencing with high-throughput sequencing (HTS) platforms can be used to efficiently interrogate the genomes of large numbers of individuals. A critical issue for research and applications using HTS data, especially from long-read platforms, is error in base calling arising from technological limits and bioinformatic algorithms. We found that the community standard long amplicon analysis (LAA) module from Pacific Biosciences is prone to substantial bioinformatic errors that raise concerns about findings based on this pipeline, prompting the need for a new method.    Results  A single molecule real-time (SMRT) sequencing-error correction and assembly pipeline, C3S-LAA, was developed for libraries of pooled amplicons. By uniquely leveraging the structure of SMRT sequence data (comprised of multiple low quality subreads from which higher quality circular consensus sequences are formed) to cluster raw reads, C3S-LAA produced accurate consensus sequences and assemblies of overlapping amplicons from single sample and multiplexed libraries. In contrast, despite read depths in excess of 100X per amplicon, the standard long amplicon analysis module from Pacific Biosciences generated unexpected numbers of amplicon sequences with substantial inaccuracies in the consensus sequences. A bootstrap analysis showed that the C3S-LAA pipeline per se was effective at removing bioinformatic sources of error, but in rare cases a read depth of nearly 400X was not sufficient to overcome minor but systematic errors inherent to amplification or sequencing.    Conclusions  C3S-LAA uses a divide and conquer processing algorithm for SMRT amplicon-sequence data that generates accurate consensus sequences and local sequence assemblies. Solving the confounding bioinformatic source of error in LAA allowed for the identification of limited instances of errors due to DNA amplification or sequencing of homopolymeric nucleotide tracts. For research and development in genomics, C3S-LAA allows meaningful conclusions and biological inferences to be made from accurately polished sequence output.    Electronic supplementary material  The online version of this article (10.1186/s12859-018-2293-0) contains supplementary material, which is available to authorized users.

bmc bioinformatics

Clustering of circular consensus sequences: accurate error correction and assembly of single molecule real-time reads from multiplexed amplicon libraries