Illumina error profiles: resolving fine-scale variation in metagenomic sequencing data.

ABSTRACT:

Background

Illumina's sequencing platforms are currently the most utilised sequencing systems worldwide. The technology has rapidly evolved over recent years and provides high throughput at low costs with increasing read-lengths and true paired-end reads. However, data from any sequencing technology contains noise and our understanding of the peculiarities and sequencing errors encountered in Illumina data has lagged behind this rapid development.

Results

We conducted a systematic investigation of errors and biases in Illumina data based on the largest collection of in vitro metagenomic data sets to date. We evaluated the Genome Analyzer II, HiSeq and MiSeq and tested state-of-the-art low input library preparation methods. Analysing in vitro metagenomic sequencing data allow

SUBMITTER: Schirmer M 

PROVIDER: S-EPMC4787001 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature