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Trivedi UH, Cézard T, Bridgett S, et al. Quality control of next-generation sequencing data without a reference. Front Genet. 2014;5:111doi: 10.3389/fgene.2014.00111.
Trivedi, U. H., Cézard, T., Bridgett, S., Montazam, A., Nichols, J., Blaxter, M., & Gharbi, K. (2014). Quality control of next-generation sequencing data without a reference. Frontiers in genetics, 5111. https://doi.org/10.3389/fgene.2014.00111
Trivedi, Urmi H, et al. "Quality control of next-generation sequencing data without a reference." Frontiers in genetics vol. 5 (2014): 111. doi: https://doi.org/10.3389/fgene.2014.00111
Trivedi UH, Cézard T, Bridgett S, Montazam A, Nichols J, Blaxter M, Gharbi K. Quality control of next-generation sequencing data without a reference. Front Genet. 2014 May 06;5:111. doi: 10.3389/fgene.2014.00111. eCollection 2014. PMID: 24834071; PMCID: PMC4018527.
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Front Genet. 2014 May 06;5:111. doi: 10.3389/fgene.2014.00111. eCollection 2014.

Quality control of next-generation sequencing data without a reference.

Frontiers in genetics

Urmi H Trivedi, Timothée Cézard, Stephen Bridgett, Anna Montazam, Jenna Nichols, Mark Blaxter, Karim Gharbi

Affiliations

  1. Edinburgh Genomics, Ashworth Laboratories, University of Edinburgh Edinburgh, UK.
  2. Edinburgh Genomics, Ashworth Laboratories, University of Edinburgh Edinburgh, UK ; Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh Edinburgh, UK.

PMID: 24834071 PMCID: PMC4018527 DOI: 10.3389/fgene.2014.00111

Abstract

Next-generation sequencing (NGS) technologies have dramatically expanded the breadth of genomics. Genome-scale data, once restricted to a small number of biomedical model organisms, can now be generated for virtually any species at remarkable speed and low cost. Yet non-model organisms often lack a suitable reference to map sequence reads against, making alignment-based quality control (QC) of NGS data more challenging than cases where a well-assembled genome is already available. Here we show that by generating a rapid, non-optimized draft assembly of raw reads, it is possible to obtain reliable and informative QC metrics, thus removing the need for a high quality reference. We use benchmark datasets generated from control samples across a range of genome sizes to illustrate that QC inferences made using draft assemblies are broadly equivalent to those made using a well-established reference, and describe QC tools routinely used in our production facility to assess the quality of NGS data from non-model organisms.

Keywords: Illumina sequencing; PCR duplicates; de novo assembly; insert size; mate pair; quality control

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