A platform-independent method for detecting errors in metagenomic sequencing data: DRISEE

We provide a novel method, DRISEE (duplicate read inferred sequencing error estimation), to assess sequencing quality (alternatively referred to as "noise" or "error") within and/or between sequencing samples. DRISEE provides positional error estimates that can be used to inform...

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Bibliographic Details
Published in:PLoS computational biology 2012-06, Vol.8 (6), p.e1002541-e1002541
Main Authors: Keegan, Kevin P, Trimble, William L, Wilkening, Jared, Wilke, Andreas, Harrison, Travis, D'Souza, Mark, Meyer, Folker
Format: Article
Language:English
Subjects:
Biology
Computational Biology
Computer applications
Data Interpretation, Statistical
Data processing
DNA sequencing
Estimates
Fidelity
Genomes
Genomics
Genomics - statistics & numerical data
High-Throughput Nucleotide Sequencing - statistics & numerical data
Humans
Mathematics
Meta-analysis
Metagenomics - statistics & numerical data
Methods
Noise
Nucleotide sequencing
Sequence Analysis - statistics & numerical data
Studies
Taxonomy
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Summary:We provide a novel method, DRISEE (duplicate read inferred sequencing error estimation), to assess sequencing quality (alternatively referred to as "noise" or "error") within and/or between sequencing samples. DRISEE provides positional error estimates that can be used to inform read trimming within a sample. It also provides global (whole sample) error estimates that can be used to identify samples with high or varying levels of sequencing error that may confound downstream analyses, particularly in the case of studies that utilize data from multiple sequencing samples. For shotgun metagenomic data, we believe that DRISEE provides estimates of sequencing error that are more accurate and less constrained by technical limitations than existing methods that rely on reference genomes or the use of scores (e.g. Phred). Here, DRISEE is applied to (non amplicon) data sets from both the 454 and Illumina platforms. The DRISEE error estimate is obtained by analyzing sets of artifactual duplicate reads (ADRs), a known by-product of both sequencing platforms. We present DRISEE as an open-source, platform-independent method to assess sequencing error in shotgun metagenomic data, and utilize it to discover previously uncharacterized error in de novo sequence data from the 454 and Illumina sequencing platforms.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1002541