The section includes information on the modelling framework, for single species qPCR data developed in Griffin, J. E., Matechou, E. Buxton, A. S., Bormpoudakis, D. and Griffiths, R. A., (2020) Modelling environmental DNA data; Bayesian variable selection accounting for false positive and false negative errors, Journal of the Royal Statistical Society: Series C (Applied Statistics), which has been implemented by Alex Diana into our freely available R Shiny eDNA app. The source code of the RShiny app and examples of how to use the app to analyse single species qPCR data are also available.

The app can be accessed on the Shiny server or, for more stable performance, it can be downloaded by going to the Download tab and following the steps outlined to run it on your own machine.

If you have any questions please email me (Dr Eleni Matechou, e.matechou@kent.ac.uk). Similarly, we would love to know if you have used the app to analyse your data so do drop me an email with the details.

Related publications

Griffin, Jim E., Eleni Matechou, Andrew S. Buxton, Dimitrios Bormpoudakis, and Richard A. Griffiths. “Modelling environmental DNA data; Bayesian variable selection accounting for false positive and false negative errors.” Journal of the Royal Statistical Society: Series C (Applied Statistics) 69, no. 2 (2020): 377-392.

Diana, Alex, Eleni Matechou, Jim E. Griffin, Andrew S. Buxton, and Richard A. Griffiths. “An RShiny app for modelling environmental DNA data: accounting for false positive and false negative observation error.” Ecography 44, no. 12 (2021): 1838-1844.

Buxton, Andrew S., Eleni Matechou, Jim E. Griffin, Alex Diana, and Richard A. Griffiths. “Optimising sampling and analysis protocols in environmental DNA studies.” Scientific reports 11, no. 1 (2021): 1-10.

Buxton, Andrew S., Alex Diana, Eleni Matechou, Jim E. Griffin, and Richard A. Griffiths. “Reliability of environmental DNA surveys to detect pond occupancy by newts at a national scale.” Scientific Reports 12, no. 1 (2022): 1-10.