The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Quantifying sequence proportions in a DNA‐based diet study using Ion Torrent amplicon sequencing: which counts count?
Abstract
A goal of many environmental DNA barcoding studies is to infer quantitative information about relative abundances of different taxa based on sequence read proportions generated by high‐throughput sequencing. However, potential biases associated with this approach are only beginning to be examined. We sequenced DNA amplified from faeces (scats) of captive harbour seals (Phoca vitulina) to investigate whether sequence counts could be used to quantify the seals’ diet. Seals were fed fish in fixed proportions, a chordate‐specific mitochondrial 16S marker was amplified from scat DNA and amplicons sequenced using an Ion Torrent PGM™. For a given set of bioinformatic parameters, there was generally low variability between scat samples in proportions of prey species sequences recovered. However, proportions varied substantially depending on sequencing direction, level of quality filtering (due to differences in sequence quality between species) and minimum read length considered. Short primer tags used to identify individual samples also influenced species proportions. In addition, there were complex interactions between factors; for example, the effect of quality filtering was influenced by the primer tag and sequencing direction. Resequencing of a subset of samples revealed some, but not all, biases were consistent between runs. Less stringent data filtering (based on quality scores or read length) generally produced more consistent proportional data, but overall proportions of sequences were very different than dietary mass proportions, indicating additional technical or biological biases are present. Our findings highlight that quantitative interpretations of sequence proportions generated via high‐throughput sequencing will require careful experimental design and thoughtful data analysis.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Quail, M., Smith, M. E., Coupland, P., Otto, T. D., Harris, S. R., Connor, T. R., Bertoni, A., Swerdlow, H. P., & Gu, Y. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-341 · Cited by 2,031 · cited 4×
“Biases in sequences recovered based on GC content have also been documented from the Ion Torrent sequencer (Quail et al. 2012).”
BackgroundInfluentialSynthetic spike-in standards for RNA-seq experiments
Jiang, L., Schlesinger, F., Davis, C. A., Zhang, Y., Li, R., Salit, M., Gingeras, T. R., & Oliver, B. (2011) · Genome Research · doi:10.1101/gr.121095.111 · Cited by 653
Hajibabaei, M., Shokralla, S., Zhou, X., Singer, G. A. C., & Baird, D. J. (2011) · PLoS ONE · doi:10.1371/journal.pone.0017497 · Cited by 584
Cited by
Piñol, J., Mir, G., Gomez‐Polo, P., & Agustí, N. (2015) · Molecular Ecology Resources · doi:10.1111/1755-0998.12355 · Cited by 423
All-Food-Seq (AFS): a quantifiable screen for species in biological samples by deep DNA sequencing
Ripp, F., Krombholz, C. F., Liu, Y., Weber, M., Schäfer, A., Schmidt, B., Köppel, R., & Hankeln, T. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-639 · Cited by 66
Dietary DNA Metabarcoding From Animal Fecal Samples
McConnell, R. D., Jarrett, C., Ferreira, D. F., Powell, L. L., Quiñones, A. L. S., Dominoni, D. M., & Welch, A. J. (2026) · Current Protocols · doi:10.1002/cpz1.70226 · Cited by 2
Metadata
- Authors
- Deagle, B. E., Thomas, A. C., Shaffer, A. K., Trites, A. W., & Jarman, S. N.
- Venue
- Molecular Ecology Resources
- Publisher
- Wiley
- Published
- 2013-04-17
- Volume
- 13
- Issue
- 4
- Pages
- 620-633
- ISSN
- 1755-098X (ISSN-L)
- 1755-0998
- OpenAlex
- W2133058864
- Cited by
- 221
- References
- 3
- FWCI
- 17.84
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Quantifying sequence proportions in a DNA‐based diet study using Ion Torrent amplicon sequencing: which counts count? https://app.cochat.ai/papers/10.1111/1755-0998.12103
- The paper
- Deagle, B. E., Thomas, A. C., Shaffer, A. K., Trites, A. W., & Jarman, S. N. (2013). Quantifying sequence proportions in a DNA‐based diet study using Ion Torrent amplicon sequencing: which counts count? Molecular Ecology Resources. https://doi.org/10.1111/1755-0998.12103
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.