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MetaShot: an accurate workflow for taxon classification of host-associated microbiome from shotgun metagenomic data

机译:MetaShot:从shot弹枪宏基因组学数据对宿主相关微生物组进行分类的准确工作流程

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摘要

SummaryShotgun metagenomics by high-throughput sequencing may allow deep and accurate characterization of host-associated total microbiomes, including bacteria, viruses, protists and fungi. However, the analysis of such sequencing data is still extremely challenging in terms of both overall accuracy and computational efficiency, and current methodologies show substantial variability in misclassification rate and resolution at lower taxonomic ranks or are limited to specific life domains (e.g. only bacteria). We present here MetaShot, a workflow for assessing the total microbiome composition from host-associated shotgun sequence data, and show its overall optimal accuracy performance by analyzing both simulated and real datasets.
机译:总结通过高通量测序进行的Shotgun宏基因组学可以深入准确地鉴定与宿主相关的总微生物组,包括细菌,病毒,原生生物和真菌。然而,就总体准确性和计算效率而言,对此类测序数据的分析仍然极具挑战性,并且当前的方法学在较低的分类学等级上显示出错误分类率和分辨率方面的巨大差异,或者仅限于特定的生命域(例如,仅细菌)。我们在这里介绍MetaShot,它是一种从宿主相关asso弹枪序列数据评估总微生物组组成的工作流程,并通过分析模拟数据集和实际数据集来显示其总体最佳准确性。

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