Physical Sciences and Mathematics Commons^™

Efficient Error Correction For Next-Generation Sequencing Of Viral Amplicons, Pavel Skums, Zoya Dimitrova, David S. Campo, Gilberto Vaughan, Livia Rossi, Joseph C. Forbi, Jonny Yokosawa, Alexander Zelikovskiy, Yury Khudyakov

Computer Science Faculty Publications

Background: Next-generation sequencing allows the analysis of an unprecedented number of viral sequence variants from infected patients, presenting a novel opportunity for understanding virus evolution, drug resistance and immune escape. However, sequencing in bulk is error prone. Thus, the generated data require error identification and correction. Most error-correction methods to date are not optimized for amplicon analysis and assume that the error rate is randomly distributed. Recent quality assessment of amplicon sequences obtained using 454-sequencing showed that the error rate is strongly linked to the presence and size of homopolymers, position in the sequence and length of the amplicon. All …