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Normalization techniques for univariate biostatistics analysis (Conference Paper)
- 1.0491880 - MBÚ 2019 RIV SK eng C - Conference Paper (international conference)
Šedivá, Blanka - Pelantová, Helena - Bugáňová, Martina
Normalization techniques for univariate biostatistics analysis (Conference Paper).
17th Conference on Applied Mathematics, APLIMAT 2018, Bratislava, Slovakia, 6 February 2018 through 8 February 2018, Code 135345. Bratislava: Slovak University of Technology in Bratislava, 2018, s. 925-932. ISBN 978-802274765-3.
[17th Conference on Applied Mathematics, APLIMAT 2018, Bratislava, Slovakia, 6 February 2018 through 8 February 2018, Code 135345. Bratislava (SK), 06.02.2018-08.02.2018]
R&D Projects: GA MŠMT(CZ) LO1509
Institutional support: RVO:61388971
Keywords : Data normalization * Metabolomics Preprocessing * Simulation
OECD category: Biology (theoretical, mathematical, thermal, cryobiology, biological rhythm), Evolutionary biology
The biostatistic processing of metabolomic data includes a number of mathematical and statistical methods. The series of preprocessing steps is necessary applied before application of the univariate or multivariate approaches for identifications of statistical significant factor. The goal of this article is using simulation Monte Carlo approach for analysis of influence of normalizations processes on the results of univariate statistical methods. In our study four methods of normalization are compared - normalization by the area under the curve (AUC), normalization to creatinine, quantile normalization and probabilistic quotient normalization (PQN). The results of simulation experiments studies have shown that PQN, quantile normalization and creatinine normalization are more robust than AUC normalization, especially in case a small number of metabolites with a large fold change is presented. From a practical point of view PQN method is recomended as the robust normalization procedure with the broad application and easy data interpretation.
Permanent Link: http://hdl.handle.net/11104/0285484
Number of the records: 1