NOREVA: normalization and evaluation of MS-based metabolomics data.

ABSTRACT: Diverse forms of unwanted signal variations in mass spectrometry-based metabolomics data adversely affect the accuracies of metabolic profiling. A variety of normalization methods have been developed for addressing this problem. However, their performances vary greatly and depend heavily on the nature of the studied data. Moreover, given the complexity of the actual data, it is not feasible to assess the performance of methods by single criterion. We therefore developed NOREVA to enable performance evaluation of various normalization methods from multiple perspectives. NOREVA integrated five well-established criteria (each with a distinct underlying theory) to ensure more comprehensive evaluation than any single criterion. It provided the most complete set of the available normalization me

SUBMITTER: Li B 

PROVIDER: S-EPMC5570188 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature