ZSeq 2.0: A fully automatic preprocessing method for next generation sequencing data

A. Alkhateeb, Iman Rezaeian, L. Rueda
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Abstract

Preprocessing is a critical step in next generation sequencing (NGS) data analysis, since any error or artifact in library preparation and the sequencing process can affect subsequent steps, leading to possibly erroneous biological conclusions. In this work, we propose ZSeq 2.0, a fully automatic NGS preprocessing method, which combines the strength of the original ZSeq method with a free of parameters scheme that automatically detects and filters out low complexity and highly biased regions, without any need for parameter adjustment. We estimate parameters by applying dynamic penalty rates to high and low GC-content sequences. We also use a labeling rule method to detect outlier sequences that have very low NUS. Some other preprocessing features have been added to ZSeq2.0, including adapter detection and low-quality nucleotides trimming at each side of the sequence. ZSeq2.0 is publicly available and can be downloaded from http://sourceforge.net/p/ZSeq/wiki/Home/.
ZSeq 2.0:下一代测序数据的全自动预处理方法
预处理是下一代测序(NGS)数据分析的关键步骤,因为文库制备和测序过程中的任何错误或伪影都可能影响后续步骤,导致可能错误的生物学结论。在这项工作中,我们提出了一种全自动NGS预处理方法ZSeq 2.0,它结合了原始ZSeq方法的强度和无参数方案,自动检测和过滤掉低复杂度和高偏差区域,无需任何参数调整。我们通过对高和低gc含量序列应用动态惩罚率来估计参数。我们还使用标记规则方法来检测具有非常低NUS的异常序列。ZSeq2.0还增加了其他一些预处理功能,包括适配器检测和序列每侧的低质量核苷酸修剪。ZSeq2.0是公开的,可以从http://sourceforge.net/p/ZSeq/wiki/Home/下载。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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