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ddPCRclust: an R package and Shiny app for automated analysis of multiplexed ddPCR data
MOTIVATION: Droplet digital PCR (ddPCR) is an emerging technology for quantifying DNA. By partitioning the target DNA into ∼20 000 droplets, each serving as its own PCR reaction compartment, a very high sensitivity of DNA quantification can be achieved. However, manual analysis of the data is time c...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6061851/ https://www.ncbi.nlm.nih.gov/pubmed/29534153 http://dx.doi.org/10.1093/bioinformatics/bty136 |
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author | Brink, Benedikt G Meskas, Justin Brinkman, Ryan R |
author_facet | Brink, Benedikt G Meskas, Justin Brinkman, Ryan R |
author_sort | Brink, Benedikt G |
collection | PubMed |
description | MOTIVATION: Droplet digital PCR (ddPCR) is an emerging technology for quantifying DNA. By partitioning the target DNA into ∼20 000 droplets, each serving as its own PCR reaction compartment, a very high sensitivity of DNA quantification can be achieved. However, manual analysis of the data is time consuming and algorithms for automated analysis of non-orthogonal, multiplexed ddPCR data are unavailable, presenting a major bottleneck for the advancement of ddPCR transitioning from low-throughput to high-throughput. RESULTS: ddPCRclust is an R package for automated analysis of data from Bio-Rad’s droplet digital PCR systems (QX100 and QX200). It can automatically analyze and visualize multiplexed ddPCR experiments with up to four targets per reaction. Results are on par with manual analysis, but only take minutes to compute instead of hours. The accompanying Shiny app ddPCRvis provides easy access to the functionalities of ddPCRclust through a web-browser based GUI. AVAILABILITY AND IMPLEMENTATION: R package: https://github.com/bgbrink/ddPCRclust; Interface: https://github.com/bgbrink/ddPCRvis/; Web: https://bibiserv.cebitec.uni-bielefeld.de/ddPCRvis/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-6061851 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-60618512018-08-07 ddPCRclust: an R package and Shiny app for automated analysis of multiplexed ddPCR data Brink, Benedikt G Meskas, Justin Brinkman, Ryan R Bioinformatics Applications Notes MOTIVATION: Droplet digital PCR (ddPCR) is an emerging technology for quantifying DNA. By partitioning the target DNA into ∼20 000 droplets, each serving as its own PCR reaction compartment, a very high sensitivity of DNA quantification can be achieved. However, manual analysis of the data is time consuming and algorithms for automated analysis of non-orthogonal, multiplexed ddPCR data are unavailable, presenting a major bottleneck for the advancement of ddPCR transitioning from low-throughput to high-throughput. RESULTS: ddPCRclust is an R package for automated analysis of data from Bio-Rad’s droplet digital PCR systems (QX100 and QX200). It can automatically analyze and visualize multiplexed ddPCR experiments with up to four targets per reaction. Results are on par with manual analysis, but only take minutes to compute instead of hours. The accompanying Shiny app ddPCRvis provides easy access to the functionalities of ddPCRclust through a web-browser based GUI. AVAILABILITY AND IMPLEMENTATION: R package: https://github.com/bgbrink/ddPCRclust; Interface: https://github.com/bgbrink/ddPCRvis/; Web: https://bibiserv.cebitec.uni-bielefeld.de/ddPCRvis/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2018-08-01 2018-03-09 /pmc/articles/PMC6061851/ /pubmed/29534153 http://dx.doi.org/10.1093/bioinformatics/bty136 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Applications Notes Brink, Benedikt G Meskas, Justin Brinkman, Ryan R ddPCRclust: an R package and Shiny app for automated analysis of multiplexed ddPCR data |
title | ddPCRclust: an R package and Shiny app for automated analysis of multiplexed ddPCR data |
title_full | ddPCRclust: an R package and Shiny app for automated analysis of multiplexed ddPCR data |
title_fullStr | ddPCRclust: an R package and Shiny app for automated analysis of multiplexed ddPCR data |
title_full_unstemmed | ddPCRclust: an R package and Shiny app for automated analysis of multiplexed ddPCR data |
title_short | ddPCRclust: an R package and Shiny app for automated analysis of multiplexed ddPCR data |
title_sort | ddpcrclust: an r package and shiny app for automated analysis of multiplexed ddpcr data |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6061851/ https://www.ncbi.nlm.nih.gov/pubmed/29534153 http://dx.doi.org/10.1093/bioinformatics/bty136 |
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