The next generation sequencers such as Illumina and SOLiD platforms generate a large amount of data, commonly above 10 Gigabytes of text files. Particularly, the SOLiD platform allows the sequencing of multiple samples in a single run (called multiplex run) through a marking
system called Barcode. This feature requires a computational process for separation of
data per sample, therefore, the sequencer provides a mixture of all samples in a single output. This process must be secure to avoid any harm that may scramble further analysis. In this context, this dissertation proposes development of a probabilistic model capable of characterizing the marking system used in multiplex sequencing. The results corroborate the adequacy of the
model obtained, which allows, among other things, identify faults in some step in the sequencing process, adapt and develop new protocols for sample preparation, and assign a grade to the reliability of data generated and guide a filtering process that respects the characteristics of each sequence, without discarding sequences useful in an arbitrary manner.
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