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      Probabilistic model based error correction in a set of various mutant sequences analyzed by next-generation sequencing.

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          Abstract

          To analyze the evolutionary dynamics of a mutant population in an evolutionary experiment, it is necessary to sequence a vast number of mutants by high-throughput (next-generation) sequencing technologies, which enable rapid and parallel analysis of multikilobase sequences. However, the observed sequences include many errors of base call. Therefore, if next-generation sequencing is applied to analysis of a heterogeneous population of various mutant sequences, it is necessary to discriminate between true bases as point mutations and errors of base call in the observed sequences, and to subject the sequences to error-correction processes. To address this issue, we have developed a novel method of error correction based on the Potts model and a maximum a posteriori probability (MAP) estimate of its parameters corresponding to the "true sequences". Our method of error correction utilizes (1) the "quality scores" which are assigned to individual bases in the observed sequences and (2) the neighborhood relationship among the observed sequences mapped in sequence space. The computer experiments of error correction of artificially generated sequences supported the effectiveness of our method, showing that 50-90% of errors were removed. Interestingly, this method is analogous to a probabilistic model based method of image restoration developed in the field of information engineering.

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          Author and article information

          Journal
          Comput Biol Chem
          Computational biology and chemistry
          1476-928X
          1476-9271
          Dec 2013
          : 47
          Affiliations
          [1 ] Exploratory Research for Advanced Technology, Japan Science and Technology Agency, Yamadaoka 1-5, Suita, Osaka, Japan.
          Article
          S1476-9271(13)00090-X
          10.1016/j.compbiolchem.2013.09.006
          24184706
          77513d0f-4737-4166-9e12-54d231e96121
          Copyright © 2013 Elsevier Ltd. All rights reserved.
          History

          Base call error,Image restoration,Quality score,Quasispecies,SMRT,Sequence analysis

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