Department of Computer Science, University of Colorado, Boulder, Colorado, USA.
Nat Methods. 2011 Jul 17;8(9):761-3. doi: 10.1038/nmeth.1650.
Contamination is a critical issue in high-throughput metagenomic studies, yet progress toward a comprehensive solution has been limited. We present SourceTracker, a Bayesian approach to estimate the proportion of contaminants in a given community that come from possible source environments. We applied SourceTracker to microbial surveys from neonatal intensive care units (NICUs), offices and molecular biology laboratories, and provide a database of known contaminants for future testing.
污染是高通量宏基因组研究中的一个关键问题，但全面解决方案的进展一直受到限制。我们提出了 SourceTracker，这是一种贝叶斯方法，可以估计给定群落中来自可能来源环境的污染物的比例。我们将 SourceTracker 应用于新生儿重症监护病房 (NICU)、办公室和分子生物学实验室的微生物调查，并提供了一个已知污染物数据库，以供未来测试。
