Abordagem probabil\'istica para an\'alise de confiabilidade de dados gerados em sequenciamentos multiplex na plataforma ABI SOLiD

TL;DR

This paper develops a probabilistic model to assess the confidence in barcode-based multiplex sequencing data from the SOLiD platform, aiding data filtering and protocol evaluation.

Contribution

A novel probabilistic approach for reliability analysis of multiplex sequencing data, improving data separation and quality assessment.

Findings

Model proved effective in confidence estimation

Facilitates data filtering and protocol evaluation

Enhances security in multiplex sequencing analysis

Abstract

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 tagging system called Barcode. This feature requires a computational process for separation of the data sample because 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, realized the need to develop a probabilistic model capable of assigning a degree of confidence in the marking system used in multiplex sequencing. The results confirmed the adequacy of the model obtained, which allows, among other things, to guide a process of filtering the data and evaluation of the sequencing protocol used.