UBC Theses and Dissertations
Automatic analysis of dual-channel Droplet Digital PCR experiments Attali, Dean
The ability to quantify the amount of DNA in a sample is an essential technique in biology and is used in many fields of research. Droplet digital polymerase chain reaction (ddPCR) is an advanced technology developed for this purpose that enables more accurate and sensitive quantification than traditional real-time PCR. In ddPCR, nucleic acid (e.g., genomic DNA) within a sample is partitioned into thousands of droplets, along with the reagents needed to amplify and detect one or more DNA target sequences. After amplification takes place in all droplets, each droplet is individually read by a two-colour fluorescence detection system to determine whether or not it contains the target sequence. ddPCR experiments utilizing both fluorescence wavelengths are termed dual-channel, while simpler experiments can make use of only one fluorescence wavelength and are thus classified as single-channel. Droplets containing amplified product exhibit high fluorescence and are said to be positive, while those without product show little or no fluorescence and are considered negative. Using this binary, or digital, classification of droplets, the number of positive and negative droplets can be counted to allow for an absolute quantification of template abundance in the starting sample. ddPCR instruments are now available commercially and their use is growing. But, there are a very limited number of tools available for downstream data analysis. The key step in ddPCR data analysis is droplet gating: using the end-point fluorescence data to gate, or classify, droplets as either positive or negative for a given template. The proprietary software provided by BioRad Inc., a ddPCR instrument manufacturer, is currently the only program available to automatically analyze dual-channel ddPCR data. However, because this analysis tool often produces poor results, many ddPCR users resort to time-consuming and subjective manual data analyses, emphasizing the clear need for new ddPCR analysis tools. In this thesis, I devise an algorithm for automatic analysis of dual-channel ddPCR data that can objectively and reproducibly perform droplet gating. The proposed analysis method has been implemented in an R package and is also available as a web application online for easy and open access to any ddPCR user.
Item Citations and Data
Attribution 4.0 International