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MicroSim Description

An analysis of the effect of systematic errors on the use of Microarray experiment

Microarray experiment's data contain errors, from various sources such as unequal quantities of starting RNA, differences in labelling or detection efficiencies between the fluorescent dyes used, and systematic biases in the measured expression levels, which may misrepresent the real signal (Quackenbush, 2002). The process of identifying and adjusting of systematic variation in intensities between samples on the same slide is known as normalization (Yang and Thorne, 2003). One widely used technical replication in two-colour spotted array analysis is dye-reversal or flip-dye analysis, which consists of duplicating labelling and hybridization by swapping the fluorescent dyes used for each RNA sample (Quackenbush, 2002).

This java application with the user-friendly graphical user interface (GUI) allows easy evaluation of errors and the rule of self-normalization method to remove the systematic errors from the experiment's data.

MicroSim generates a number of fragments with random lengths, then these fragments will be evolved to mutated fragments using a range of evolutionary distances. Four nucleotide substitution models, including Jukes-Cantor, Kimura 2 parameters, Hasegawa-Kishino-Yano (HKY), and Tamura-Nei are implemented. Therefore depends on chosen model different adjustable kappa (Transition/Transversion ratio) and base frequency will be applied. Then using start and mutated fragments as red and green spots, true intensity (logged ratio) of spots will be calculated and it might be stored. User may adjust the additive and multiplicative errors and MicroSim computes the normalized intensity logged ratio using self-normalization method and dye-flip technique. The environment temperature, which can affect on binding probability of fragments, is also adjustable.

MicroSim results will be saved into xls file that can be used directly by statistical software like Microsoft Excel or SPSS to visualize and analyze.

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