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HECTOR: a parallel multistage homopolymer spectrum based error corrector for 454 sequencing data.

ABSTRACT: BACKGROUND: Current-generation sequencing technologies are able to produce low-cost, high-throughput reads. However, the produced reads are imperfect and may contain various sequencing errors. Although many error correction methods have been developed in recent years, none explicitly targets homopolymer-length errors in the 454 sequencing reads. RESULTS: We present HECTOR, a parallel multistage homopolymer spectrum based error corrector for 454 sequencing data. In this algorithm, for the first time we have investigated a novel homopolymer spectrum based approach to handle homopolymer insertions or deletions, which are the dominant sequencing errors in 454 pyrosequencing reads. We have evaluated the performance of HECTOR, in terms of correction quality, runtime and parallel scalability, using both simulated and real pyrosequencing datasets. This performance has been further compared to that of Coral, a state-of-the-art error corrector which is based on multiple sequence alignment and Acacia, a recently published error corrector for amplicon pyrosequences. Our evaluations reveal that HECTOR demonstrates comparable correction quality to Coral, but runs 3.7× faster on average. In addition, HECTOR performs well even when the coverage of the dataset is low. CONCLUSION: Our homopolymer spectrum based approach is theoretically capable of processing arbitrary-length homopolymer-length errors, with a linear time complexity. HECTOR employs a multi-threaded design based on a master-slave computing model. Our experimental results show that HECTOR is a practical 454 pyrosequencing read error corrector which is competitive in terms of both correction quality and speed. The source code and all simulated data are available at: http://hector454.sourceforge.net.

SUBMITTER: Wirawan A

PROVIDER: S-EPMC4023493 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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HECTOR: a parallel multistage homopolymer spectrum based error corrector for 454 sequencing data.

Wirawan Adrianto A Harris Robert S RS Liu Yongchao Y Schmidt Bertil B Schröder Jan J

BMC bioinformatics 20140506

<h4>Background</h4>Current-generation sequencing technologies are able to produce low-cost, high-throughput reads. However, the produced reads are imperfect and may contain various sequencing errors. Although many error correction methods have been developed in recent years, none explicitly targets homopolymer-length errors in the 454 sequencing reads.<h4>Results</h4>We present HECTOR, a parallel multistage homopolymer spectrum based error corrector for 454 sequencing data. In this algorithm, fo ...[more]

PMID: 24885381

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Project description:MotivationIllumina Sequencing data can provide high coverage of a genome by relatively short (most often 100 bp to 150 bp) reads at a low cost. Even with low (advertised 1%) error rate, 100 × coverage Illumina data on average has an error in some read at every base in the genome. These errors make handling the data more complicated because they result in a large number of low-count erroneous k-mers in the reads. However, there is enough information in the reads to correct most of the sequencing errors, thus making subsequent use of the data (e.g. for mapping or assembly) easier. Here we use the term "error correction" to denote the reduction in errors due to both changes in individual bases and trimming of unusable sequence. We developed an error correction software called QuorUM. QuorUM is mainly aimed at error correcting Illumina reads for subsequent assembly. It is designed around the novel idea of minimizing the number of distinct erroneous k-mers in the output reads and preserving the most true k-mers, and we introduce a composite statistic π that measures how successful we are at achieving this dual goal. We evaluate the performance of QuorUM by correcting actual Illumina reads from genomes for which a reference assembly is available.ResultsWe produce trimmed and error-corrected reads that result in assemblies with longer contigs and fewer errors. We compared QuorUM against several published error correctors and found that it is the best performer in most metrics we use. QuorUM is efficiently implemented making use of current multi-core computing architectures and it is suitable for large data sets (1 billion bases checked and corrected per day per core). We also demonstrate that a third-party assembler (SOAPdenovo) benefits significantly from using QuorUM error-corrected reads. QuorUM error corrected reads result in a factor of 1.1 to 4 improvement in N50 contig size compared to using the original reads with SOAPdenovo for the data sets investigated.AvailabilityQuorUM is distributed as an independent software package and as a module of the MaSuRCA assembly software. Both are available under the GPL open source license at http://www.genome.umd.edu.Contactgmarcais@umd.edu.

Project description:BackgroundThe invention of the Genome Sequence 20 DNA Sequencing System (454 parallel sequencing platform) has enabled the rapid and high-volume production of sequence data. Until now, however, individual emulsion PCR (emPCR) reactions and subsequent sequencing runs have been unable to combine template DNA from multiple individuals, as homologous sequences cannot be subsequently assigned to their original sources.MethodologyWe use conventional PCR with 5'-nucleotide tagged primers to generate homologous DNA amplification products from multiple specimens, followed by sequencing through the high-throughput Genome Sequence 20 DNA Sequencing System (GS20, Roche/454 Life Sciences). Each DNA sequence is subsequently traced back to its individual source through 5'tag-analysis.ConclusionsWe demonstrate that this new approach enables the assignment of virtually all the generated DNA sequences to the correct source once sequencing anomalies are accounted for (miss-assignment rate<0.4%). Therefore, the method enables accurate sequencing and assignment of homologous DNA sequences from multiple sources in single high-throughput GS20 run. We observe a bias in the distribution of the differently tagged primers that is dependent on the 5' nucleotide of the tag. In particular, primers 5' labelled with a cytosine are heavily overrepresented among the final sequences, while those 5' labelled with a thymine are strongly underrepresented. A weaker bias also exists with regards to the distribution of the sequences as sorted by the second nucleotide of the dinucleotide tags. As the results are based on a single GS20 run, the general applicability of the approach requires confirmation. However, our experiments demonstrate that 5'primer tagging is a useful method in which the sequencing power of the GS20 can be applied to PCR-based assays of multiple homologous PCR products. The new approach will be of value to a broad range of research areas, such as those of comparative genomics, complete mitochondrial analyses, population genetics, and phylogenetics.

Project description:454 sequencing technology is a promising approach for characterizing HIV-1 populations and for identifying low frequency mutations. The utility of 454 technology for determining allele frequencies and linkage associations in HIV infected individuals has not been extensively investigated. We evaluated the performance of 454 sequencing for characterizing HIV populations with defined allele frequencies.We constructed two HIV-1 RT clones. Clone A was a wild type sequence. Clone B was identical to clone A except it contained 13 introduced drug resistant mutations. The clones were mixed at ratios ranging from 1% to 50% and were amplified by standard PCR conditions and by PCR conditions aimed at reducing PCR-based recombination. The products were sequenced using 454 pyrosequencing. Sequence analysis from standard PCR amplification revealed that 14% of all sequencing reads from a sample with a 50:50 mixture of wild type and mutant DNA were recombinants. The majority of the recombinants were the result of a single crossover event which can happen during PCR when the DNA polymerase terminates synthesis prematurely. The incompletely extended template then competes for primer sites in subsequent rounds of PCR. Although less often, a spectrum of other distinct crossover patterns was also detected. In addition, we observed point mutation errors ranging from 0.01% to 1.0% per base as well as indel (insertion and deletion) errors ranging from 0.02% to nearly 50%. The point errors (single nucleotide substitution errors) were mainly introduced during PCR while indels were the result of pyrosequencing. We then used new PCR conditions designed to reduce PCR-based recombination. Using these new conditions, the frequency of recombination was reduced 27-fold. The new conditions had no effect on point mutation errors. We found that 454 pyrosequencing was capable of identifying minority HIV-1 mutations at frequencies down to 0.1% at some nucleotide positions.Standard PCR amplification results in a high frequency of PCR-introduced recombination precluding its use for linkage analysis of HIV populations using 454 pyrosequencing. We designed a new PCR protocol that resulted in a much lower recombination frequency and provided a powerful technique for linkage analysis and haplotype determination in HIV-1 populations. Our analyses of 454 sequencing results also demonstrated that at some specific HIV-1 drug resistant sites, mutations can reliably be detected at frequencies down to 0.1%.

Dataset Information

HECTOR: a parallel multistage homopolymer spectrum based error corrector for 454 sequencing data.

Publications

HECTOR: a parallel multistage homopolymer spectrum based error corrector for 454 sequencing data.

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