Electrical Penetration Graph (EPG) is a technique used to monitor insect feeding behavior. Studying voltage waveforms in EPG data allows one to analyze the insect-host relationship and gain insights into what makes a suitable host.
To facilitate the analysis of EPG data, EPGminer
contains various
functions for working with voltage time series data as well as ANA
annotation files from manual annotation software.
The primary utility of using EPGminer
for analysis is the ability to
calculate Frequency and Relative Amplitude. Frequency is calculated
using the Fourier Transform to extract the main constituent frequencies
in each waveform. Relative amplitude is a measure of the voltage
amplitude for each waveform.
Another aspect of EPGminer
is data visualization via plots. The
plotting functions are all in the format plot_x where x denotes the
type of plot. The types of plots currently supported are: voltage time
series, labeled time-series, Fourier transformed data, frequency
boxplot, and two types of pie charts.
An accompanying Shiny app, available as both a web version (https://epgdata.shinyapps.io/epgminer_app/) and locally through R, includes a streamlined version of the package functionality focusing on the main calculations and visuals.
To cite (with DOI) please use:
Elizabeth Chun. (2022). LylChun/EPGminer: EPGminer (v1.0.0). Zenodo.
EPGminer
can be run on any standard computer with enough memory to
perform the necessary operations. It was primarily tested on a computer
with 8 GB of RAM which is amply sufficient.
The package was developed and primarily tested on Windows 10 Version 20H2. It has also been tested on macOS Monterey Version 12.1.
This R package was developed using R version 4.1.0. It depends on R (>=4.0.0) as well as specific package Imports listed in the DESCRIPTION file.
A streamlined version of EPGminer
is available as a Shiny application.
The EPGminer
App web version may be launched via the user’s web
browser with no installation or other software dependencies required.
The app has been tested in the following browsers:
Chrome Version 99.0.4844.51 Edge Version 99.0.1150.39 Safari Version 15.2
Note that due to server limitations, the web version is limited in memory and should not be used for datasets that exceed 100mb at most.
The EPGminer
app local version must be installed with the R package
itself and System Requirements are as noted above.
To use the EPGminer
package, users must have R installed on their
computer. This may be accomplished by going to
https://cran.r-project.org/, downloading, and installing the
appropriate version of R for the given operating system. Installation of
R should take around 1 minute.
Once R has been properly installed, the EPGminer
package may be
installed from GitHub as follows.
The EPGminer
package can be installed from GitHub using devtools
via
the following code in R. Installation should take around 30 seconds. To
install the package without vignettes, set build_vignettes = FALSE
(install time will be faster, however this means the vignettes
referenced in “Demo” and “Instructions for use” will not be installed).
if (!require(devtools)){
install.packages("devtools")
}
devtools::install_github("LylChun/EPGminer", build_vignettes = TRUE)
For a demo of EPGminer
with instructions, expected output, and
expected run time, please see the “EPGminerDemo” vignette which can be
found on the package website
here
The vignette may also be accessed in R via:
vignette("EPGminerDemo")
Note that due to the size of EPG datasets, the data is included in a
separate R package called epgdata
which can be found
here
Use of the software for EPG data analysis involves data
reading/processing, labeling, and calculation of metrics. For an example
script showing how we used EPGminer
on our data, please see the
“EPGminerReprex” vignette
here
or via R:
vignette("EPGminerReprex")
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