A new pipeline for the normalization and pooling of metabolomics data

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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Détails bibliographiques
Auteurs principaux: 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
Format: Journal article
Langue:English
Publié: MDPI 2021

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