基因组
推论
计算机科学
计算生物学
数据挖掘
基因
生物
人工智能
遗传学
作者
Gavin M. Douglas,Vincent J. Maffei,Jesse Zaneveld,Svetlana N. Yurgel,James R. Brown,Christopher M. Taylor,Curtis Huttenhower,Morgan G. I. Langille
摘要
One major limitation of microbial community marker gene sequencing is that it does not provide direct information on the functional composition of sampled communities. Here, we present PICRUSt2 ( https://github.com/picrust/picrust2 ), which expands the capabilities of the original PICRUSt method 1 to predict the functional potential of a community based on marker gene sequencing profiles. This updated method and implementation includes several improvements over the previous algorithm: an expanded database of gene families and reference genomes, a new approach now compatible with any OTU-picking or denoising algorithm, and novel phenotype predictions. Upon evaluation, PICRUSt2 was more accurate than PICRUSt1 and other current approaches overall. PICRUSt2 is also now more flexible and allows the addition of custom reference databases. We highlight these improvements and also important caveats regarding the use of predicted metagenomes, which are related to the inherent challenges of analyzing metagenome data in general.
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