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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# iglu
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[](https://cran.r-project.org/package=iglu)[](https://CRAN.R-project.org/package=iglu)
[](https://github.com/irinagain/iglu/actions)
[](https://github.com/irinagain/iglu/actions/workflows/R-CMD-check.yaml)
[](https://app.codecov.io/gh/irinagain/iglu?branch=master)
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iglu: Interpreting data from Continuous Glucose Monitors (CGMs)
====================================================================
The R package 'iglu' provides functions for outputting relevant metrics for data collected from Continuous Glucose Monitors (CGM). For reference, see ["Interpretation of continuous glucose monitoring data: glycemic variability and quality of glycemic control." Rodbard (2009)](https://doi.org/10.1089/dia.2008.0132). For more information on the package, see [package website](https://irinagain.github.io/iglu/).
To cite:
* Broll S, Urbanek J, Buchanan D, Chun E, Muschelli J, Punjabi N and Gaynanova I (2021). [Interpreting blood glucose data with R package iglu.](https://doi.org/10.1371/journal.pone.0248560) *PLoS One*, Vol. 16, No. 4, e0248560.
* Broll S, Buchanan D, Chun E, Muschelli J, Fernandes N, Seo J, Shih J, Urbanek J, Schwenck J, Gaynanova I (2021). iglu: Interpreting Glucose Data from Continuous Glucose Monitors. R package version 3.0.0.
iglu comes with two example datasets: example_data_1_subject and example_data_5_subject. These data are collected using Dexcom G4 CGM on subjects with Type II diabetes. Each dataset follows the structure iglu's functions are designed around. Note that the 1 subject data is a subset of the 5 subject data. See the examples below for loading and using the data.
Installation
------------
The R package 'iglu' is available from CRAN, use the commands below to install the most recent Github version.
```{r, eval = FALSE}
# Plain installation
devtools::install_github("irinagain/iglu") # iglu package
# For installation with vignette
devtools::install_github("irinagain/iglu", build_vignettes = TRUE)
```
Example
-------
```{r}
library(iglu)
data(example_data_1_subject) # Load single subject data
## Plot data
# Use plot on dataframe with time and glucose values for time series plot
plot_glu(example_data_1_subject)
# Summary statistics and some metrics
summary_glu(example_data_1_subject)
in_range_percent(example_data_1_subject)
above_percent(example_data_1_subject, targets = c(80,140,200,250))
j_index(example_data_1_subject)
conga(example_data_1_subject)
# Load multiple subject data
data(example_data_5_subject)
plot_glu(example_data_5_subject, plottype = 'lasagna', datatype = 'average')
below_percent(example_data_5_subject, targets = c(80,170,260))
mage(example_data_5_subject)
```
Shiny App
------------
Shiny App can be accessed locally via
```{r, eval = FALSE}
library(iglu)
iglu_shiny()
```
or globally at [https://irinagain.shinyapps.io/shiny_iglu/](https://irinagain.shinyapps.io/shiny_iglu/). As new functionality gets added, local version will be slightly ahead of the global one.