How to maximize power for differential expression analysis in discovery omics through experimental design

Brenden Dufaulta George & Fay Yee Centre for Healthcare Innovation, University of Manitoba, Winnipeg, MB, CanadaView further author information

Richard D. LeDucb Children’s Hospital Research Institute of Manitoba, Winnipeg, MB, Canada;c Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB, CanadaCorrespondence[email protected]
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René P. Zahedic Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB, Canada;d Department of Internal Medicine, University of Manitoba, Winnipeg, MB, Canada;e Manitoba Centre for Proteomics and Systems Biology, Winnipeg, MB, Canada;f Paul Albrechtsen Research Institute, Cancer Care Manitoba, Winnipeg, MB, CanadaCorrespondence[email protected]
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Declaration of interests

RP Zahedi is CEO of MRM Proteomics Inc. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

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Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

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Funding

This paper was funded by the University of Manitoba and Shared Health.

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How to maximize power for differential expression analysis in discovery omics through experimental design

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