mahshaaban/colocr repository overview

⁠colocr

An R package for conducting co-localization analysis.

⁠Overview

A few R packages are available for conducting image analysis, which is a very wide topic. As a result, some of use might feel at loss when all they want to do is a simple co-localization calculations on a small number of microscopy images. This package provides a simple straight forward workflow for loading images, choosing regions of interest (ROIs) and calculating co-localization statistics. Included in the package, is a shiny app⁠ that can be invoked locally to interactively select the regions of interest in a semi-automatic way. The package is based on the R package imager⁠.

⁠Installing colocr

To install the development version from github⁠ use the following.

devtools::install_github('MahShaaban/colocr')

⁠Getting started

To get started, load the required packages and the images. Then, apply the appropriate parameters for choosing the regions of interest using the parameter_choose. Finally, check the appropriatness of the parameters by highlighting the ROIs on the image.

# load libraries
library(imager)
library(colocr)

# load images
fl <- system.file('extdata', 'Image0001_.jpg', package = 'colocr')
img <- load.image(fl)

# choose parameters
px <- parameter_choose(img, threshold = 90)

# highlight chosen region of interest
par(mar=rep(0, 4))
plot(img, axes = FALSE)
highlight(px)

The same can be acheived interactively using an accompanying shiny app. To launch the app run.

run_app()

The reset of the anlysis depends on the particular kind of images. Now, colocr implements two simple colocalizations statistics; Pearson's Coefficeint Correlation (PCC)⁠ and the Manders Overlap Coefficient (MOC)⁠.

To apply both measures of correlation, we first load the images from the two channels and call coloc_test.

corr <- coloc_test(img, px, type = 'all')

corr$p  # PCC
corr$r  # MPC

The same analysis and more can be conducted using a web interface for the package available here⁠

⁠Acknowledgement

• The vignette images from Lai Huyen Trang⁠
• The test examples from Colocalization Benchmark Source (CBS)⁠
• The implementation of the co-localization statistics from Dunn et al.⁠

⁠More

browseVignettes('colocr')