KARGA: Multi-platform Toolkit for k-mer-based Antibiotic Resistance Gene Analysis of High-throughput Sequencing Data.
KARGA: Multi-platform Toolkit for k-mer-based Antibiotic Resistance Gene Analysis of High-throughput Sequencing Data.
复制标题
DOI：
10.1109/bhi50953.2021.9508479
复制
发表时间：
2021-07
期刊：
影响因子：
--
通讯作者：
Marini S
中科院分区：
文献类型：
--
作者：
Prosperi M;Marini S
高通量测序广泛用于微生物宏基因组样品中的菌株检测和抗生素抗性表征。目前的分析工具使用策展的抗生素抗性基因（ARG）数据库来对单个测序读段或组装的重叠群进行分类。然而，由于基因组重排和突变，从原始读取数据中识别ARG可能是耗时的（特别是如果需要组装或比对）和具有挑战性的。在这里，我们提出了基于k-mer的抗生素基因抗性分析仪（KARGA），一个多平台的Java工具包，用于从宏基因组短读数据中识别ARG。KARGA不执行比对;它使用有效的双重查找策略，对假阳性进行统计过滤，并提供单个读段分类以及数据库耐药基因组的覆盖。在模拟数据上，KARGA的抗生素耐药类别召回率在10%以内的错误/突变率为99.89%，在10%和25%之间的错误/突变率为83.37%，而在具有重排的ARG上为99.92%。根据经验数据，KARGA提供的命中评分（≥1.5倍）高于AMRPlusPlus、DeepARG和MetaMARC。KARGA的运行速度也比其他所有工具都快（比AMRPlusPlus快2倍，比DeepARG快7倍，比MetaMARC快100倍以上）。KARGA在MIT许可下可在https://github.com/DataIntellSystLab/KARGA上获得。
High-throughput sequencing is widely used for strain detection and characterization of antibiotic resistance in microbial metagenomic samples. Current analytical tools use curated antibiotic resistance gene (ARG) databases to classify individual sequencing reads or assembled contigs. However, identifying ARGs from raw read data can be time consuming (especially if assembly or alignment is required) and challenging, due to genome rearrangements and mutations. Here, we present the k-mer-based antibiotic gene resistance analyzer (KARGA), a multi-platform Java toolkit for identifying ARGs from metagenomic short read data. KARGA does not perform alignment; it uses an efficient double-lookup strategy, statistical filtering on false positives, and provides individual read classification as well as covering of the database resistome. On simulated data, KARGA’s antibiotic resistance class recall is 99.89% for error/mutation rates within 10%, and of 83.37% for error/mutation rates between 10% and 25%, while it is 99.92% on ARGs with rearrangements. On empirical data, KARGA provides higher hit score (≥1.5-fold) than AMRPlusPlus, DeepARG, and MetaMARC. KARGA has also faster runtimes than all other tools (2x faster than AMRPlusPlus, 7x than DeepARG, and over 100x than MetaMARC). KARGA is available under the MIT license at https://github.com/DataIntellSystLab/KARGA.