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XY-Meta: A High-Efficiency Search Engine for Large-Scale Metabolome Annotation with Accurate FDR Estimation.

Dehua LiBinghang LiuHancheng ZhengXu XiaoZhenyu LiEnhui LuanWei LiYaling YangYalan WangQiaoyun LongJiaping SongGong Zhang
Published in: Analytical chemistry (2020)
FDR control has been a huge challenge for large-scale metabolome annotation. Although recent research indicated that the target-decoy strategy could be implemented to estimate FDR, it is hard to perform FDR control due to the difficulty of getting a reliable decoy database because of the complex fragmentation mechanism of metabolites and ubiquitous isomers. To tackle this problem, we developed a decoy generation method, which generates forged spectra from the reference target database by preserving the original reference signals to simulate the presence of isomers of metabolites. Benchmarks on GNPS data sets in Passatutto showed that the decoy database generated by our method is closer to the actual FDR than other methods, especially in the low FDR range (0-0.05). Large-scale metabolite annotation on 35 data sets showed that strict FDR reduced the number of annotated metabolites but increased the spectral efficiency, indicating the necessity of quality control. We recommended that the FDR threshold should be set to 0.01 in large-scale metabolite annotation. We implemented decoy generation, database search, and FDR control into a search engine called XY-Meta. It facilitates large-scale metabolome annotation applications.
Keyphrases
  • ms ms
  • rna seq
  • quality control
  • high efficiency
  • electronic health record
  • big data
  • optical coherence tomography
  • emergency department
  • magnetic resonance imaging
  • computed tomography
  • magnetic resonance