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Sep 2014
Last activity
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Jun 2015
Publication ID: ICY-U8L5N4

Short Description

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

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).

Changelog

• Version 0.0.1.2 • Released on: 2015-06-12 14:57:05
Description:

implements the points simulation in 3D

• Version 0.0.1.1 • Released on: 2014-09-02 16:00:55
• Version 0.0.1.0 • Released on: 2014-09-01 13:18:37