Simulation Toolbox for 3D-FISH Spot-Counting Algorithms

Abstract

Fluorescent in situ hybridization (FISH) is a molecular diagnostic technique in which a fluorescent labeled probe hybridizes to a target nucleotide sequence of DNA. Upon excitation, each chromosome containing the target sequence produces a fluorescent signal (spot). New technology provides a stack of images on multiple focal planes throughout a tissue sample. Multiple-focal-plane imaging helps to overcome the biases and imprecision inherent in single-focal-plane methods. New algorithms are being proposed to take advantage of the multiple focal planes. This paper presents a simulation toolbox that generates synthetic spots, both signal and noise, with which to evaluate algorithm performance. By using the toolbox, preset algorithm parameters can be tuned or optimized. Two critical issues for any algorithm are the sampling rate, which is the number of focal planes used, and the parameters for the filter that determines which detected spots are signal and which are noise. One would like to use a minimal number of focal planes for reasons of both time and cost, and one would like to have a noise filter that optimally balances the passing and non-passing of signal and noise spots. As demonstrated, it is possible to go further and calibrate the noise filter so that the expected number of counted spots, both signal and noise, is approximately equal to the actual number of signal spots.