Removing Noise From Pyrosequenced Amplicons

Background: In many environmental genomics applications a homologous region of DNA from a diverse sample is first amplified by PCR and then sequenced. The next generation sequencing technology, 454 pyrosequencing, has allowed much larger read numbers from PCR amplicons than ever before. This has revolutionised the study of microbial diversity as it is now possible to sequence a substantial fraction of the 16S rRNA genes in a community. However, there is a growing realisation that because of the large read numbers and the lack of consensus sequences it is vital to distinguish noise from true sequence diversity in this data. Otherwise this leads to inflated estimates of the number of types or operational taxonomic units (OTUs) present. Three sources of error are important: sequencing error, PCR single base substitutions and PCR chimeras. We present AmpliconNoise, a development of the PyroNoise algorithm that is capable of separately removing 454 sequencing errors and PCR single base err...

• Type: Journal
• Year: 2011
• Where: BMCBI
• Authors: Christopher Quince, Anders Lanzén, Russell J. Davenport, Peter J. Turnbaugh
• Keywords: Artificial Intelligence, Base Error, BMCBI 2011, PCR Single Base, Read Numbers