Harmonization of quality metrics and power calculation in multi-omic studies
Type
ArticleAuthors
Tarazona, SoniaBalzano-Nogueira, Leandro
Gómez-Cabrero, David
Schmidt, Andreas
Imhof, Axel

Hankemeier, Thomas
Tegner, Jesper

Westerhuis, Johan A.

Conesa, Ana

Date
2020-06-18Online Publication Date
2020-06-18Print Publication Date
2020-12Submitted Date
2018-07-27Permanent link to this record
http://hdl.handle.net/10754/663712
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Multi-omic studies combine measurements at different molecular levels to build comprehensive models of cellular systems. The success of a multi-omic data analysis strategy depends largely on the adoption of adequate experimental designs, and on the quality of the measurements provided by the different omic platforms. However, the field lacks a comparative description of performance parameters across omic technologies and a formulation for experimental design in multi-omic data scenarios. Here, we propose a set of harmonized Figures of Merit (FoM) as quality descriptors applicable to different omic data types. Employing this information, we formulate the MultiPower method to estimate and assess the optimal sample size in a multi-omics experiment. MultiPower supports different experimental settings, data types and sample sizes, and includes graphical for experimental design decision-making. MultiPower is complemented with MultiML, an algorithm to estimate sample size for machine learning classification problems based on multi-omic data.Citation
Tarazona, S., Balzano-Nogueira, L., Gómez-Cabrero, D., Schmidt, A., Imhof, A., Hankemeier, T., … Conesa, A. (2020). Harmonization of quality metrics and power calculation in multi-omic studies. Nature Communications, 11(1). doi:10.1038/s41467-020-16937-8Sponsors
This work has been funded by FP7 STATegra project agreement 306000 and Spanish MINECO grant BIO2012–40244. In addition, work in the Imhof lab has been funded by the (DFG; CIPSM and SFB1064). The work of L.B.-N. has been funded by the University of Florida Startup funds.Publisher
Springer Science and Business Media LLCJournal
Nature CommunicationsPubMed ID
32555183Additional Links
http://www.nature.com/articles/s41467-020-16937-8https://www.nature.com/articles/s41467-020-16937-8.pdf
ae974a485f413a2113503eed53cd6c53
10.1038/s41467-020-16937-8
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