JACoPx - Modified JACoP Plugin to include RWC coefficients

The following java excutable jar file (jacopx_.jar) is a modification of the co-localization plugin (JACoP) available for ImageJ, which has been extended to include Rank Weighted Co-localization (RWC) coefficients. This RWC component of this code is open source and can be used, and modified as specified under the GNU General Public License.

     Download the java jar file here.

NOTE:

• Download and install ImageJ (http://rsbweb.nih.gov/ij/download.html) if you do not have one. 
• To install this code, download the ImageJ JACOPx plugin jar from the link provided above. Save the jar file to plugins folder of your ImageJ installation.
•  To run the code, restart ImageJ and select two images for co-localization. Under the plugins option, select "JACOPx" to run the modified plugin.
•  RWC coefficients can be selected under the available RWC1 and RWC2 coefficients option.
•  A new image with the Rank Weighting as pixel values is generated for reference. This image may also be used for downstream segmentation algorithms.
•  The manual thresholding tool within this plugin is not used. Instead, 15% of the maximum intensity in each channel is used for thresholding.

     JACoPx is an extension of the publicly available JACoP plugin (Coredelieres and Bolte, 2006) for ImageJ.  

     Author: Vasanth R. Singan (VRSingan @ lbl.gov)

Synthetic Dataset - 1

     The synthetic_Dataset_1 folder contains 10 sub-folders, labelled according to the levels of co-occurrence between the image pairs. Within each of these folders are 22 files, representing 11 'green' channel images and 11 'red' channel images. The number appended to each image represents the % of correlation between the images. These data were used to produce the plots shown in Figures 1 and 2 of the manuscript.

     Download the zipped synthetic dataset file here.

Synthetic Dataset - 2

     The synthetic_Dataset_2 folder contains 8 files representing 4 'green' channel images and 4 'red'channel images corresponding to the panels A-D in Figure 3 of the manuscript. 

     Download the zipped synthetic dataset file here.

Please cite our work:

Dual channel rank-based intensity weighting for quantitative co-localization of microscopy images

VR Singan, TR Jones, KM Curran, JC Simpson

BMC bioinformatics 12 (1), 407

Quantitative image analysis approaches for probing rab gtpase localization and function in mammalian cells

VR Singan, K Handzic, JC Simpson

Biochemical Society Transactions 40 (6), 1389

Implementation of the Rank-Weighted Co-localization (RWC) algorithm in multiple image analysis platforms for quantitative analysis of microscopy images

VR Singan, JC Simpson

Source Code for Biology and Medicine 11 (2)