基因组
生物
计算生物学
虚假关系
微生物群
进化生物学
人体微生物群
仿形(计算机编程)
人类微生物组计划
功能多样性
基因
遗传学
生态学
生物信息学
计算机科学
操作系统
机器学习
作者
Eric A. Franzosa,Lauren J. McIver,Ali Rahnavard,Luke Thompson,Melanie Schirmer,George Weingart,Karen Schwarzberg Lipson,Rob Knight,J. Gregory Caporaso,Nicola Segata,Curtis Huttenhower
出处
期刊:Nature Methods
[Springer Nature]
日期:2018-10-23
卷期号:15 (11): 962-968
被引量:1247
标识
DOI:10.1038/s41592-018-0176-y
摘要
Functional profiles of microbial communities are typically generated using comprehensive metagenomic or metatranscriptomic sequence read searches, which are time-consuming, prone to spurious mapping, and often limited to community-level quantification. We developed HUMAnN2, a tiered search strategy that enables fast, accurate, and species-resolved functional profiling of host-associated and environmental communities. HUMAnN2 identifies a community’s known species, aligns reads to their pangenomes, performs translated search on unclassified reads, and finally quantifies gene families and pathways. Relative to pure translated search, HUMAnN2 is faster and produces more accurate gene family profiles. We applied HUMAnN2 to study clinal variation in marine metabolism, ecological contribution patterns among human microbiome pathways, variation in species’ genomic versus transcriptional contributions, and strain profiling. Further, we introduce ‘contributional diversity’ to explain patterns of ecological assembly across different microbial community types. HUMAnN2 uses a tiered sequence search to provide rapid and accurate species-level functional profiles of microbial communities from metagenomic and metatranscriptomic data.
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