Efficient error correction and haplotypes reconstruction for deep sequencing of hepatitis c amplicons

Abstract

We present two new highly efficient pyrosequencing error correction algorithms: (i) k-mer – based error correction (KEC); and (ii) empirical frequency threshold (ET). Both were compared to the recently published clustering algorithm SHORAH to evaluate the relative performance using 24 experimental datasets obtained by 454-sequencing of amplicons with known sequences. We found that all three algorithms showed similar performance in terms of finding true haplotypes, but KEC and ET methods significantly outperformed SHORAH both in terms of their ability to remove false haplotypes and to estimate the frequency of true ones.