Analysing extremely small sized ratio datasets

Piero Ricchiuto*, Judy C.G. Sng, Wilson Wen Bin Goh

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The naïve use of expression ratios in high-throughput biological studies can greatly limit analytical outcome especially when sample size is small. In the worst-case scenario, with only one reference and one test state each (often due to the severe lack of study material); such limitations make it difficult to perform statistically meaningful analysis. Workarounds include the single sample Z-test or through network inference. Here, we describe a complementary plot-based approach for analysing such extremely small sized ratio (ESSR) data - a generalisation of the Bland-Altman plot, which we shall refer to as the Dodeca-Panels. Included in this paper is an R implementation of the Dodeca-Panels method.

Original languageEnglish
Pages (from-to)268-280
Number of pages13
JournalInternational Journal of Bioinformatics Research and Applications
Volume11
Issue number3
DOIs
Publication statusPublished - 2015
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2015 Inderscience Enterprises Ltd.

ASJC Scopus Subject Areas

  • Biomedical Engineering
  • Health Informatics
  • Clinical Biochemistry
  • Health Information Management

Keywords

  • Bioinformatics
  • Clinical translation
  • Drug and biomarker discovery
  • Protein responders
  • Proteomics
  • Small ratios dataset

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