Robust volcano plot: Identification of differential metabolites in the presence of outliers

Nishith Kumar, Md Aminul Hoque, Masahiro Sugimoto

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)

Abstract

Background: The identification of differential metabolites in metabolomics is still a big challenge and plays a prominent role in metabolomics data analyses. Metabolomics datasets often contain outliers because of analytical, experimental, and biological ambiguity, but the currently available differential metabolite identification techniques are sensitive to outliers. Results: We propose a kernel weight based outlier-robust volcano plot for identifying differential metabolites from noisy metabolomics datasets. Two numerical experiments are used to evaluate the performance of the proposed technique against nine existing techniques, including the t-test and the Kruskal-Wallis test. Artificially generated data with outliers reveal that the proposed method results in a lower misclassification error rate and a greater area under the receiver operating characteristic curve compared with existing methods. An experimentally measured breast cancer dataset to which outliers were artificially added reveals that our proposed method produces only two non-overlapping differential metabolites whereas the other nine methods produced between seven and 57 non-overlapping differential metabolites. Conclusion: Our data analyses show that the performance of the proposed differential metabolite identification technique is better than that of existing methods. Thus, the proposed method can contribute to analysis of metabolomics data with outliers. The R package and user manual of the proposed method are available at https://github.com/nishithkumarpaul/Rvolcano.

Original languageEnglish
Article number128
JournalBMC bioinformatics
Volume19
Issue number1
DOIs
Publication statusPublished - 2018 Apr 11
Externally publishedYes

Keywords

  • Classical volcano plot
  • Differential metabolites
  • Fold change
  • Metabolomics
  • Receiver operating characteristic (ROC) curve

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Robust volcano plot: Identification of differential metabolites in the presence of outliers'. Together they form a unique fingerprint.

Cite this