A new pipeline for the normalization and pooling of metabolomics data

Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Sp...

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Библиографические подробности
Главные авторы: Viallon, V, His, M, Rinaldi, S, Breeur, M, Gicquiau, A, Hemon, B, Overvad, K, Tjønneland, A, Rostgaard-Hansen, AL, Rothwell, JA, Lecuyer, L, Severi, G, Kaaks, R, Johnson, T, Schulze, MB, Palli, D, Agnoli, C, Panico, S, Tumino, R, Ricceri, F, Verschuren, WMM, Engelfriet, P, Onland-Moret, C, Vermeulen, R, Nøst, TH, Urbarova, I, Zamora-Ros, R, Rodriguez-Barranco, M, Amiano, P, Huerta, JM, Ardanaz, E, Melander, O, Ottoson, F, Vidman, L, Rentoft, M, Schmidt, JA, Travis, RC, Weiderpass, E, Johansson, M, Dossus, L, Jenab, M, Gunter, MJ, Lorenzo Bermejo, J, Scherer, D, Salek, RM, Keski-Rahkonen, P, Ferrari, P
Формат: Journal article
Язык:English
Опубликовано: MDPI 2021

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