オーラルセッション
- 第4日 5月18日（金） 15:45～16:05 C会場（星雲2）
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4C-O2-P-1545 PDF
When is a Biomarker not a biomarker? The problems of interpreting statistical data in Discovery ‘Omics analysis.
Discovery omics analysis is a vital first step in a full biomarker discovery workflow since it generates a list of potential compound or protein biomarkers to go through into the more targeted validation and confirmation steps. The high complexity of discovery omics means that great care must be taken in the interpretation of the statistical results in order to avoid false discoveries. Model data is used here to illustrate how “real" and “false" candidate biomarker discoveries can be made and to show their contrasting characteristics. It's also shown how false discoveries can be avoided by correct interpretation of the data and by applying false discovery tests to the final lists of biomarker candidates.