artemis: an R package for eDNA analysis

The artemis package was created to aid in the design and analysis of eDNA survey studies by offering a custom suite of models for eDNA sampling and qPCR data. It implements a set of Bayesian latent-variable, truncated data models which are fit using Stan.

Installation

install.packages("artemis")

Testing your installation

If your installation of artemis and its dependencies was successful, the following code should run without error (although you may see warning messages from rstan about Bulk/Tail Effective Samples Sizes being too low). If the first or second model returns an error that seems to have something to do with your c++ compiler, you may need to follow instructions to edit your Makevars or Makevars.win file.

library(artemis)

model_fit = eDNA_lm(Cq ~ scale(Distance_m) + scale(Volume_mL), 
                    data = eDNA_data,
                    std_curve_alpha = 21.2, std_curve_beta = -1.5)

model_fit2 = eDNA_lmer(Cq ~ scale(Distance_m) + scale(Volume_mL) + (1|FilterID),
                       eDNA_data,
                       std_curve_alpha = 21.2, std_curve_beta = -1.5)

Installing artemis from source

Installing artemis from source on Windows is not currently well-supported; we recommend installing from the pre-compiled binary if you're on Windows. If you're on MacOS or Linux and you prefer to install from source, then go ahead and do that with your function/utility of choice (devtools::install_github(), utils::install.packages(type = "source"), R CMD INSTALL, etc.).
If you have sub-architecture you're really in to customizing, the source code is here, go nuts.

Basic use

Please refer to the Getting Started with the artemis package vignette, which covers most of the functionality of artemis.

Additional vignettes are forthcoming!

Reporting bugs

Please report all bugs via an issue at the package repo.