RESUMO
Slippage is an important sequencing problem that can occur in EST projects. However, very few studies have addressed this. We propose three new methods to detect slippage artifacts: arithmetic mean method, geometric mean method, and echo coverage method. Each method is simple and has two different strategies for processing sequences: suffix and subsequence. Using the 291,689 EST sequences produced in the SUCEST project, we performed comparative tests between our proposed methods and the SUCEST method. The subsequence strategy is better than the suffix strategy, because it is not anchored at the end of the sequence, so it is more flexible to find slippage at the beginning of the EST. In a comparison with the SUCEST method, the advantage of our methods is that they do not discard the majority of the sequences marked as slippage, but instead only remove the slipped artifact from the sequence. Based on our tests the echo coverage method with subsequence strategy shows the best compromise between slippage detection and ease of calibration.
Assuntos
Humanos , Análise de Sequência de DNA/métodos , Etiquetas de Sequências Expressas , Modelos Genéticos , Saccharum/genética , Técnicas Genéticas , Rearranjo Gênico , Replicação do DNARESUMO
A great effort has been made to identify and map a large set of single nucleotide polymorphisms. The goal is to determine human DNA variants that contribute most significantly to population variation in each trait. Different algorithms and software packages, such as PolyBayes and PolyPhred, have been developed to address this problem. We present strategies to detect single nucleotide polymorphisms, using chromatogram analysis and consensi of multiple aligned sequences. The algorithms were tested using HIV datasets, and the results were compared with those produced by PolyBayes and PolyPhred using the same dataset. Our algorithms produced significantly better results than these two software packages.