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Measuring sequencer size bias using REcount: a novel method for highly accurate Illumina sequencing-based quantification
Quantification of DNA sequence tags from engineered constructs such as plasmids, transposons, or other transgenes underlies many functional genomics measurements. Typically, such measurements rely on PCR followed by next-generation sequencing. However, PCR amplification can introduce significant qua...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6489363/ https://www.ncbi.nlm.nih.gov/pubmed/31036053 http://dx.doi.org/10.1186/s13059-019-1691-6 |
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author | Gohl, Daryl M. Magli, Alessandro Garbe, John Becker, Aaron Johnson, Darrell M. Anderson, Shea Auch, Benjamin Billstein, Bradley Froehling, Elyse McDevitt, Shana L. Beckman, Kenneth B. |
author_facet | Gohl, Daryl M. Magli, Alessandro Garbe, John Becker, Aaron Johnson, Darrell M. Anderson, Shea Auch, Benjamin Billstein, Bradley Froehling, Elyse McDevitt, Shana L. Beckman, Kenneth B. |
author_sort | Gohl, Daryl M. |
collection | PubMed |
description | Quantification of DNA sequence tags from engineered constructs such as plasmids, transposons, or other transgenes underlies many functional genomics measurements. Typically, such measurements rely on PCR followed by next-generation sequencing. However, PCR amplification can introduce significant quantitative error. We describe REcount, a novel PCR-free direct counting method. Comparing measurements of defined plasmid pools to droplet digital PCR data demonstrates that REcount is highly accurate and reproducible. We use REcount to provide new insights into clustering biases due to molecule length across different Illumina sequencers and illustrate the impacts on interpretation of next-generation sequencing data and the economics of data generation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-019-1691-6) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6489363 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-64893632019-05-08 Measuring sequencer size bias using REcount: a novel method for highly accurate Illumina sequencing-based quantification Gohl, Daryl M. Magli, Alessandro Garbe, John Becker, Aaron Johnson, Darrell M. Anderson, Shea Auch, Benjamin Billstein, Bradley Froehling, Elyse McDevitt, Shana L. Beckman, Kenneth B. Genome Biol Method Quantification of DNA sequence tags from engineered constructs such as plasmids, transposons, or other transgenes underlies many functional genomics measurements. Typically, such measurements rely on PCR followed by next-generation sequencing. However, PCR amplification can introduce significant quantitative error. We describe REcount, a novel PCR-free direct counting method. Comparing measurements of defined plasmid pools to droplet digital PCR data demonstrates that REcount is highly accurate and reproducible. We use REcount to provide new insights into clustering biases due to molecule length across different Illumina sequencers and illustrate the impacts on interpretation of next-generation sequencing data and the economics of data generation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-019-1691-6) contains supplementary material, which is available to authorized users. BioMed Central 2019-04-29 /pmc/articles/PMC6489363/ /pubmed/31036053 http://dx.doi.org/10.1186/s13059-019-1691-6 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Method Gohl, Daryl M. Magli, Alessandro Garbe, John Becker, Aaron Johnson, Darrell M. Anderson, Shea Auch, Benjamin Billstein, Bradley Froehling, Elyse McDevitt, Shana L. Beckman, Kenneth B. Measuring sequencer size bias using REcount: a novel method for highly accurate Illumina sequencing-based quantification |
title | Measuring sequencer size bias using REcount: a novel method for highly accurate Illumina sequencing-based quantification |
title_full | Measuring sequencer size bias using REcount: a novel method for highly accurate Illumina sequencing-based quantification |
title_fullStr | Measuring sequencer size bias using REcount: a novel method for highly accurate Illumina sequencing-based quantification |
title_full_unstemmed | Measuring sequencer size bias using REcount: a novel method for highly accurate Illumina sequencing-based quantification |
title_short | Measuring sequencer size bias using REcount: a novel method for highly accurate Illumina sequencing-based quantification |
title_sort | measuring sequencer size bias using recount: a novel method for highly accurate illumina sequencing-based quantification |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6489363/ https://www.ncbi.nlm.nih.gov/pubmed/31036053 http://dx.doi.org/10.1186/s13059-019-1691-6 |
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