Metagenomic profiling, predicting the presence and relative abundances of microbes in a sample, is a critical first step in microbiome analysis. Alignment-based approaches are often considered accurate yet computationally infeasible. Here, we present a novel method, Metalign, that performs efficient and accurate alignment-based metagenomic profiling. We use a novel containment min hash approach to pre-filter the reference database prior to alignment and then process both uniquely aligned and multi-aligned reads to produce accurate abundance estimates. In performance evaluations on both real and simulated datasets, Metalign is the only method evaluated that maintained high performance and competitive running time across all datasets.

中文翻译：

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Metalign：通过包含最小哈希进行高效的基于比对的宏基因组分析

宏基因组分析预测样品中微生物的存在和相对丰度，是微生物组分析的关键第一步。基于对齐的方法通常被认为是准确的，但在计算上不可行。在这里，我们提出了一种新方法 Metalign，它可以执行高效且准确的基于比对的宏基因组分析。我们使用一种新颖的包含最小哈希方法在比对之前预过滤参考数据库，然后处理唯一比对和多重比对读取以产生准确的丰度估计。在真实数据集和模拟数据集的性能评估中，Metaalign 是唯一在所有数据集上保持高性能和有竞争力的运行时间的评估方法。