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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%"
)
```
# rvent
<!-- badges: start -->
[](https://github.com/https://github.com/c1au6i0/rvent)
[](https://github.com/c1au6i0/rvent/commits/master)
<!-- badges: end -->
The goal of rvent is to summarize, analyze and plot experimental data recorded with the [SCIREQ pletysmograph](https://www.scireq.com/).
The package was originally developed for being used by people with limited knowledge of *R*. For example, when function parameter `inter = TRUE`, dialog windows allow to interactively insert all others required parameters.
The `rvent` packaged is used by a **the shiny app** ([link](https://rden.shinyapps.io/rvent_app/), [github](https://github.com/c1au6i0/rvent_app)).
## Installation
``` r
# install.packages("devtools")
devtools::install_github("c1au6i0/rvent")
```
## Example
This is a basic example of how to use the package:
```{r example, eval=FALSE}
library(rvent)
# open dialog to select the directory with iox files to import
# import them and make them tidy
sess1 <- import_session()
# open a series of interactive windows to select bin and baseline duration,
# missing info and drug treatments. Summarizes the data in an excel file
summarize_vent(sess1)
# for each subject creates a plot with 20 facets corresponding to the 20 recorded
# variables
session_plots(sess1)
```
You can bind tighter multiple excel-summary files into a single file by moving them into the same folder and then running:
```{r eval=FALSE}
bind_summary()
```
This is the example plot generated by `session_plot` for a subject Alex_DeLarge that received milk-plus.
```{r plot, fig.width=12, fig.height=12, echo=FALSE, message=FALSE}
library(rvent)
library(tidyverse)
load("R/sysdata.rda")
class(dat_vent) <- "data.frame"
x <- dat_vent %>%
filter(subj == "rat1") %>%
mutate(drug = "milk-plus", subj = "Alex_DeLarge")
class(x) <- c("vent", "data.frame")
autoplot.vent(x, fsave = FALSE)
```
### Accepted files and recording
The `rvent` package extract some of the metadata from the subject name and comments provide in the output file. Thus, it is important to follow some rules for recording sessions.
**---Subject name---**
*Subject name* needs to contain a numeric ID (rest of the name will be discarded) followed by a drug name.
These are all examples of accepted formats for subject 1 receiving 3 mg/kg of milk:
```
1 milk 3 mg/kg # prefered
1_milk_3_mg/kg
1 milk
1 milk ignoredinfo
```
These are examples of not accepted formats:
```
milk 1
milk rat1
```
**---Comments---**
*Comments* are used to identify the injection time.
When one or more subjects receive an injection, use the SCIREQ software to add a comment in the form "ID DRUG DOSE UNIT".
For example, these are the accepted formats for a session in which subjects 1, 2 and 3 received 3 mg/kg of milk:
```
1 2 3 milk 3 mg/kg # prefered
rat 1 and 2 and 3 milk 3 mg/kg
rat1_2_3_milk 3 mg/kg
rat1 2 3 milk
```
**If dose or unit are not inserted**, the package will ask you to fill that info.
Note, that **subjects are expected to get one injection per session.**
For each subject, the time of the injection is identified by:
* extracting rows with comments and columns relative to time, date and comments.
* extracting from that dataframe, subject `ID DRUG DOSE UNIT`.
* clean it up to have a single subject for each row.
* inner-joining it with the dataframe of data by `ID` and `DATE`(this last one introduced in *v0.0.2.100*).
**This means that you can analyze together different sessions of the same subject, as long as they are not from the same day.**
**---Example of iox file---**
This is an example of a [recording file](https://1drv.ms/t/s!Am3aUTxhPMS8iM43UVMJXhO4mNCecw?e=b9gszt) (containing randomly generated data).