1International Research Training Group “Computational Methods for the Analysis of the Diversity and Dynamics of Genomes” and Biodata Mining Group, Faculty of Technology and Center for Biotechnology, Bielefeld University, Bielefeld, Germany2Terry Fox Laboratory, BC Cancer Agency, Vancouver, Canada3Department Medical Genetics, University of British Columbia, Vancouver, Canada
Checking for direct PDF access through Ovid
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.