Abstract
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.Contact gmarcais@umd.edu.
Highlights
While second generation sequencing technologies have progressed tremendously and offer ever longer reads with low overall sequencing error rate, correcting errors in reads remains an important pre-processing step in de novo genome assembly
The de Bruijn graph made from raw reads is likely larger and more complicated, making the assembly process more difficult and error prone
We evaluate the error correction software by error correcting the reads of three organisms, two bacterial genomes and a mammalian genome, for which a finished sequence is available: Rhodobacter sphareoides (Mackenzie et al, 2001), Staphylococcus aureus, and Mus musculus (Waterston et al, 2002)
Summary
While second generation sequencing technologies have progressed tremendously and offer ever longer reads with low overall sequencing error rate, correcting errors in reads remains an important pre-processing step in de novo genome assembly. For Illumina sequencing, the base quality degrades toward the 3’ ends of the reads, one can trim the reads either by a fixed amount or based on the quality values reported by the sequencing machine. These simple trimming schemes will reduce the number of erroneous bases, it still leaves many errors in the reads and needlessly discards a lot of valid sequence.
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