# OAtools
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## Overview
OAtools is an R package for analyzing OpenArray gene expression experiments
motivated by a desire to support open-source and shareable data analyses in
public health and research environments.
OAtools offers a public API for the following:
- converting run data into ergonomic Bioconductor class objects
- analyzing OpenArray experiments by fitting logistic models to PCR curves
- rendering pre-packaged plots to visualize experiment outcomes
- generating an HTML document summarizing run results for reporting
## Installation
You can install the development version of OAtools from the [UW Virology NGS GitHub](https://github.com/uwvirology-ngs):
``` r
# Install the devtools package
install.packages("devtools")
# Install the development version of OAtools from the UW Virology NGS GitHub
devtools::install_github(
repo = "uwvirology-ngs/OAtools",
dependencies = TRUE,
build_vignettes = TRUE
)
```
## Documentation
The full documentation for OAtools may be found in the package vignette. Once OAtools is installed, the vignette is accessible by running the following command in the R console:
``` r
browseVignettes(package = "OAtools")
```
## Example
Here we demonstrate a minimal example of the OAtools workflow. Please refer to
the package vignette for more comprehensive documentation.
### Importing Run Data
Once data has been exported in excel format from QuantStudio 12K Flex Software,
we can load the experiment into a SummarizedExperiment container.
``` r
# save filepath to example OpenArray gene expression run data
path = system.file(
"extdata",
"oa_gene_expression_1.xlsx",
package = "OAtools"
)
# transform the run data into a SummarizedExperiment
se <- excelToSE(excel_path = path)
```
### Analyzing PCR with logistic regressions
Next, we run an optimizer to fit logistic regressions to each amplification
curve and use the resulting model equation to derive PCR results. A pre-made
key defines thresholds that separate curves into positive and negative results.
```r
# optimize model curves to each PCR reaction
se <- computeModels(
se = se,
assay_name = "fluo_reporter"
)
# save filepath to assay target key
key_path = system.file(
"extdata",
"target_threshold_key.xlsx",
package = "OAtools"
)
# assign a PCR result according to the key
se <- determinePCRResults(
se = se,
key_path = key_path
)
```
### Communicating the Results
Finally, we dynamically generate an HTML run report to summarize the outcome
of the experiment.
```r
# generate a .html report from the run data
generateReport(se = se)
```
## Interoperability
*OAtools* supports interoperability with the twin packages *ReadqPCR* and
*NormqPCR*, which normalize RT-qPCR gene expression data from platforms
like OpenArray. Refer to the package vignette for example code or the official
[NormqPCR Documentation](https://www.bioconductor.org/packages/release/bioc/html/NormqPCR.html)
for normalization workflows.
## Shiny app
To invoke the built-in Shiny GUI for running OAtools, run the following in the
R console:
```r
shiny::runApp(buildApp())
```
## Getting Help
For feature suggestions or bug reports, please file an issue on the project [GitHub](https://github.com/uwvirology-ngs/OAtools/issues)
