Metaboprep: an R package for preanalysis data description and processing.

ABSTRACT:

Motivation

Metabolomics is an increasingly common part of health research and there is need for preanalytical data processing. Researchers typically need to characterize the data and to exclude errors within the context of the intended analysis. Whilst some preprocessing steps are common, there is currently a lack of standardization and reporting transparency for these procedures.

Results

Here, we introduce metaboprep, a standardized data processing workflow to extract and characterize high quality metabolomics datasets. The package extracts data from preformed worksheets, provides summary statistics and enables the user to select samples and metabolites for their analysis based on a set of quality metrics. A report summarizing quality metrics and the influence of available

SUBMITTER: Hughes DA 

PROVIDER: S-EPMC8963298 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature