title: MapReduce for accurate error correction of next-generation sequencing data.
abstract: BACKGROUND
  Next-generation sequencing platforms have produced huge amounts of sequence data. This is revolutionizing every aspect of genetic and genomic research. However, these sequence datasets contain quite a number of machine-induced errors-e.g. errors due to substitution can be as high as 2.5%. Existing error-correction methods are still far from perfect. In fact, more errors are sometimes introduced than correct corrections, especially by the prevalent k-mer based methods. The existing methods have also made limited exploitation of on-demand cloud computing.
  
  
  RESULTS
  We introduce an error-correction method named MEC, which uses a two-layered MapReduce technique to achieve high correction performance. In the first layer, all the input sequences are mapped to groups to identify candidate erroneous bases in parallel. In the second layer, the erroneous bases at the same position are linked together from all the groups for making statistically reliable corrections. Experiments on real and simulated datasets show that our method outperforms existing methods remarkably. Its per-position error rate is consistently the lowest, and the correction gain is always the highest.
  
  
  METHODS
  The source code is available at bioinformatics.gxu.edu.cn/ngs/mec.
  
  
  BACKGROUND
  wongls@comp.nus.edu.sg or jinyan.li@uts.edu.au.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: School of Computing and Electronic Information, Guangxi University, Nanning 530004, China.|Taihe Hospital, Hubei University of Medicine, Hubei 442000, China.
authors.forename: Liang
authors.initials: L
authors.lastname: Zhao
authors.affiliation: School of Computing and Electronic Information, Guangxi University, Nanning 530004, China.
authors.forename: Qingfeng
authors.initials: Q
authors.lastname: Chen
authors.affiliation: Taihe Hospital, Hubei University of Medicine, Hubei 442000, China.
authors.forename: Wencui
authors.initials: W
authors.lastname: Li
authors.affiliation: School of Computing and Electronic Information, Guangxi University, Nanning 530004, China.
authors.forename: Peng
authors.initials: P
authors.lastname: Jiang
authors.affiliation: School of Computing, National University of Singapore, Singapore 117417, Singapore.
authors.forename: Limsoon
authors.initials: L
authors.lastname: Wong
authors.affiliation: Advanced Analytics Institute and Centre for Health Technologies, University of Technology Sydney, Broadway, NSW 2007, Australia.
authors.forename: Jinyan
authors.initials: J
authors.lastname: Li
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D059014:High-Throughput Nucleotide Sequencing; D015203:Reproducibility of Results; D017422:Sequence Analysis, DNA / Q000379:methods*