Updating Quality Scores During HMM-based Correction of ILLUMINA Next Generation Sequencing

Speaker: Haijuan Zhang

Abstract: PREMIER -(PRobabilistic Error-correction using Markov Inference in Errored Reads) has an advantage over comparable error correctors because it is a fully probabilistic model. As a result, it is possible to directly estimate the probability of error after correcting the error in ILLUMINA Next Generation Sequencing. However, PREMIER does not update the quality score after error correction. Phred quality score is a measure of the quality of the identification of the nucleobases generated by automated DNA Sequencing. We propose and show a hypothesis that the updated quality score in PREMIER is closer to the Phred quality score than a un-update quality score.