From trash to treasure: detecting unexpected contamination in unmapped NGS data
From trash to treasure: detecting unexpected contamination in unmapped NGS data
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DOI：
10.1186/s12859-019-2684-x
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发表时间：
2019-04-18
影响因子：
3
通讯作者：
Guarracino, Mario Rosario
中科院分区：
文献类型：
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作者：
Sangiovanni, Mara;Granata, Ilaria;Guarracino, Mario Rosario
下一代测序（NGS）实验产生数百万个短序列，这些序列映射到参考基因组，在基因组、转录组和表观基因组水平上提供生物学见解。通常情况下，与参考基因组正确对应的读取量在70%到90%之间，在某些情况下，会留下一致比例的未映射序列。这种“错位”可归因于低质量碱基或样本reads与参考基因组之间的序列差异。对于更好地评估整个实验的质量和检查可能的下游或上游外源核酸“污染”来说，调查未定位reads的来源绝对是重要的。在这里，我们提出了DecontaMiner，这是一种揭示未映射读段中存在污染序列的工具。它使用减法方法来识别细菌、真菌和病毒的基因组污染。DecontaMiner生成几个输出文件来跟踪所有处理的读取，并提供其特征的完整报告。对样本间的微生物基因组进行了质量匹配计数和比较。DecontaMiner构建一个离线HTML页面，其中包含摘要统计数据和情节。后者是使用最先进的D3 javascript库获得的。去污剂主要用于检测人RNA-Seq数据中的污染。该软件可在http://www-labgtp.na.icar.cnr.it/decontaminer.ConclusionsDecontaMiner免费获得，是一种设计和开发的工具，用于调查未绘制的NGS数据中是否存在污染序列。它可以提示测序样本中存在污染生物体，可能来自实验室污染，也可能来自其生物来源，在这两种情况下，都可以认为值得进一步调查和实验验证。DecontaMiner的新颖性主要体现在其易于与NGS数据分析的标准程序集成，同时提供完整、可靠和自动的管道。
BackgroundNext Generation Sequencing (NGS) experiments produce millions of short sequences that, mapped to a reference genome, provide biological insights at genomic, transcriptomic and epigenomic level. Typically the amount of reads that correctly maps to the reference genome ranges between 70% and 90%, leaving in some cases a consistent fraction of unmapped sequences. This 'misalignment' can be ascribed to low quality bases or sequence differences between the sample reads and the reference genome. Investigating the source of the unmapped reads is definitely important to better assess the quality of the whole experiment and to check for possible downstream or upstream 'contamination' from exogenous nucleic acids.ResultsHere we propose DecontaMiner, a tool to unravel the presence of contaminating sequences among the unmapped reads. It uses a subtraction approach to identify bacteria, fungi and viruses genome contamination. DecontaMiner generates several output files to track all the processed reads, and to provide a complete report of their characteristics. The good quality matches on microorganism genomes are counted and compared among samples. DecontaMiner builds an offline HTML page containing summary statistics and plots. The latter are obtained using the state-of-the-art D3 javascript libraries. DecontaMiner has been mainly used to detect contamination in human RNA-Seq data. The software is freely available at http://www-labgtp.na.icar.cnr.it/decontaminer.ConclusionsDecontaMiner is a tool designed and developed to investigate the presence of contaminating sequences in unmapped NGS data. It can suggest the presence of contaminating organisms in sequenced samples, that might derive either from laboratory contamination or from their biological source, and in both cases can be considered as worthy of further investigation and experimental validation. The novelty of DecontaMiner is mainly represented by its easy integration with the standard procedures of NGS data analysis, while providing a complete, reliable, and automatic pipeline.