## Helpers for working with inForm data

phenoptr contains functions that make it easier to read and analyze data tables and images created by Akoya Biosciences’ inForm® software.

phenoptr is part of the Akoya Biosciences Phenoptics™ family of Quantitative Pathology Research Solutions. For more information visit the Phenoptics™ home page.

## Installation

phenoptr requires the R environment for statistical computing, version 3.3.0 or higher. To install R, visit the R download page. The RStudio IDE is highly recommended as well.

3. Start RStudio.
4. Install phenoptr from GitHub. In the RStudio console, copy and paste or type these commands (press Enter after each line):
install.packages("devtools")
devtools::install_github("akoyabio/phenoptr")
1. When requested, enter 1 (Yes) to install BiocInstaller.

### Optional packages

Two optional packages are recommended in specific circumstances.

• 2x2 fields from inForm The Akoya Biosciences fork of the tiff package includes support for tiled images and allows phenoptr to work with 2x2 component images from inForm. See the installation instructions in the package README file.
• Spatial metrics The Akoya Biosciences rtree package dramatically speeds calculation and reduces memory requirements of spatial metrics such as nearest neighbors and count within. See the installation instructions in the package README file.

## Getting Started

These Tutorials introduce the most important features of phenoptr.

For examples showing aggregation across multiple inForm fields and multiple slides, see the Tutorials in the phenoptrExamples package.

### Learning R

R is a powerful and popular environment for data manipulation and statistical analysis. Many learning resources are available online.

phenoptr is designed to work in harmony with packages in the tidyverse.

• A tibble (also known as data_frame) is the preferred representation of tabular data.
• dplyr, purrr and the pipe operator (%>%) are used extensively in package code and examples.

If you’d like to learn more about the tidyverse packages, a good place to start is Garrett Grolemund and Hadley Wickham’s book, available free online at R for data science. If you are new to R, the book’s Introduction will help you get started.

## Full documentation

See the Reference section of the documentation for details on individual functions.

To cite package phenoptr in publications use:

Kent S Johnson (2019). phenoptr: inForm Helper Functions. R package version 0.2.2.
https://akoyabio.github.io/phenoptr/