基因组
软件
生物
生态学
成对比较
计算机科学
计算生物学
数据科学
人工智能
生物化学
基因
程序设计语言
作者
Donovan H. Parks,Robert G. Beiko
出处
期刊:Bioinformatics
[Oxford University Press]
日期:2010-02-03
卷期号:26 (6): 715-721
被引量:818
标识
DOI:10.1093/bioinformatics/btq041
摘要
Metagenomics is the study of genetic material recovered directly from environmental samples. Taxonomic and functional differences between metagenomic samples can highlight the influence of ecological factors on patterns of microbial life in a wide range of habitats. Statistical hypothesis tests can help us distinguish ecological influences from sampling artifacts, but knowledge of only the P-value from a statistical hypothesis test is insufficient to make inferences about biological relevance. Current reporting practices for pairwise comparative metagenomics are inadequate, and better tools are needed for comparative metagenomic analysis.We have developed a new software package, STAMP, for comparative metagenomics that supports best practices in analysis and reporting. Examination of a pair of iron mine metagenomes demonstrates that deeper biological insights can be gained using statistical techniques available in our software. An analysis of the functional potential of 'Candidatus Accumulibacter phosphatis' in two enhanced biological phosphorus removal metagenomes identified several subsystems that differ between the A.phosphatis stains in these related communities, including phosphate metabolism, secretion and metal transport.Python source code and binaries are freely available from our website at http://kiwi.cs.dal.ca/Software/STAMP CONTACT: beiko@cs.dal.caSupplementary data are available at Bioinformatics online.
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