====== TAPAS Tutorial : Colocalisation ======

===== Introduction =====
In this tutorial we will learn some basic analysis functions of [[plugin:utilities:tapas_:integrated_framework_for_automated_processing_and_analysis:start|TAPAS]]. We will learn how to use the **multiColoc** module to compute **co-localisation** between two populations. Please check you understand the basics of [[plugin:utilities:tapas_:integrated_framework_for_automated_processing_and_analysis:start|TAPAS]]. You can also check this [[plugin:utilities:tapas_tutorial_:segmentation:start|tutorial on segmentation with TAPAS]]. 

==== Input data ====
Here we will need two labelled images as inputs, the **multiColoc** module will then find the pairs of objects co-localising and compute the volume of their intersection. First we will need to get one image as input and save it as a temporary file. 

{{:plugin:stacks:3d_ij_suite:coloc-a.png?direct&256|First image}}

<code> 
// We use here the raw data as the reference image and
// we assume the first labelled image has the same name 
// as the reference image with -spots2
process:input
name:?name?-spots2

// we then save this file locally
// here in the ImageJ/Fiji folder
process:save
dir:?ij?
file:?name?-coloc2.tif
</code>

We can then get the other image as input.

{{:plugin:stacks:3d_ij_suite:coloc-b.png?direct&256|First image}}

<code> 
// We use here the raw data as the reference image and
// we assume the first labelled image has the same name 
// as the reference image with -spots1
process:input
name:?name?-spots1
</code>

==== Computing co-localisation ====
We then use the **multiColoc** module to compute co-localisation between the two spots populations. The module will require to specify the path to the other labelled image, in our case the image //spots2// that we saved locally, and the path to save the results. 

<code>
// Multi-colocalisation between two images
// we need the path to the other label image
// here image spots1
// results will be saved locally
process:multiColoc
dirLabel:?ij?
fileLabel:?name?-spots2.tif
dir:?ij?
file:?name?-coloc.csv
</code>

{{:plugin:stacks:3d_ij_suite:coloc-resultstable.png?direct&256|Results table for co-localisation}}

The first column **label** refers to the objects in the first image, called //A//, here //-spots1//, with their label value. The second column **O1** will refer to the label of a co-localised object in the second image, called //B//, here //-spots2//. The third column **V1** is the intersection volume between the two objects co-localising, in number of pixels. The fourth column **P1** is the ratio of the intersection volume over the  volume of object in //A//, giving an idea of the importance of the co-localisation. If the object in //A// co-localises with a second object, the column **O2**, **V2** and **P2** will give information about the co-localisation between object in //A// and a second object in image //B//. 

In our example, the object with value 295 in image //A// will co-localise with object with value 1124 in image //B//, with an intersection volume of only 3 pixels. The object 295 in image //A// does not co-localise with another object in image //B//. 

==== Saving the results and cleaning temporary files ====

The results are saved as temporary files, we must //attach// them to the original raw data. The module **attach** will //attach// results file to the image within Omero or will copy the results in the same folder as the original image if data are on files. 

<code>
// attach results file to data in omero or on files
process:attach
dir:?ij?
file:?name?-coloc.csv
</code>

Finally we can delete the temporary file. 
<code>
// delete temporary spot2 file
process:delete
dir:?ij?
file:?name?-spots2.tif
</code>