Distinguishing low frequency mutations from RT-PCR and sequence errors in viral deep sequencing data.

ABSTRACT:

Background

RNA viruses have high mutation rates and exist within their hosts as large, complex and heterogeneous populations, comprising a spectrum of related but non-identical genome sequences. Next generation sequencing is revolutionising the study of viral populations by enabling the ultra deep sequencing of their genomes, and the subsequent identification of the full spectrum of variants within the population. Identification of low frequency variants is important for our understanding of mutational dynamics, disease progression, immune pressure, and for the detection of drug resistant or pathogenic mutations. However, the current challenge is to accurately model the errors in the sequence data and distinguish real viral variants, particularly those that exist at low frequency,

SUBMITTER: Orton RJ 

PROVIDER: S-EPMC4425905 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature