Need help or advice ? Come to the Icy club ! - Every Wenesday morning from 9h30 to 12h30 - Francois Jacob Building - Main hall - Pasteur
Register

User reviews

This plugin is not rated yet


Please log-in to post a review

Colocalization Simulator

by Thibault Lagache

Create two synthetic sequences with given numbers of spots and colocalization properties (percentage, distance mean and standard deviation)

Publication Id
ICY-U8L5N4
See technical details
View complete changelog

Documentation

This plugin is designed to create two sequences with variable level of molecule colocalization.

Image model 

We used a Mixed Poisson-Gaussian model to generate synthetic fluorescent images (see chapter 1 of the PhD thesis of N. Chenouard, Telecom Paris & Institut Pasteur). In this model, the intensity I[x,y] at pixel location [x,y] is equal to

I[x,y]= gain*U[x,y] + N(x,y)

where U is a random Poisson variable and N an additive white Gaussian noise. The mean λ[x,y] of the Poisson variable U varies spatially: λ[x,y]=P[x,y]+B, P[x,y] being the sum of the intensity of the particles generated in [x,y] and B a constant background value. gain=1 is the gain of the acquisition system. Finally, we assumed an additive model for the intensity of the particles, the intensity of each particle following a spatial Gaussian distribution (Gaussian approximation of the Point Spread Function (PSF)). 

Parameters

1- Syntheric image parameters

- Sequence height: Height (in pixels) of generated sequences

- Sequence width: Width (in pixels) of generated sequences

- Sequence length: Time length of generated sequences. Spot positions are independent from each other between images at different time points.

- Number of Spots 1Number of spots in each image of the first sequence. Spot positions are uniformly distributed.

- Number of Spots 2 Number of spots in each image of the first sequence. Spot positions (that do not colocalize!) are uniformly distributed.

- Min. Spot Intensity/Max. Spot Intensity: Min/Max. intensity of spots (the intensity of each spot is uniformly distributed between min. and max.)

- Mean Gaussian noiseMean value of the additive Gaussian noise N (see model above)

- Poisson noise: Background value B of the Poisson noise (see model above)

2- Colocalization parameters

- Percentage of colocalization: Percentage of spots 2 that colocalize with spots 1

- Mean distance of colocalization: Mean distance between colocalized spots: The distance between the center of mass of 2 colocalized spots is modeled with a Gaussian variable (Thomas process).

- Std. distance of colocalization: Standard deviation of the distance between colocalized spots: The distance between the center of mass of 2 colocalized spots is modeled with a Gaussian variable (Thomas process).