metaboprep: an R package for preanalysis data description and processing | Zendy

David A. Hughes | Zendy; Kurt Taylor | Zendy; Nancy McBride | Zendy; Matthew A. Lee | Zendy; Dan Mason | Zendy; Debbie A. Lawlor | Zendy; Nicholas J. Timpson | Zendy; Laura J. Corbin | Zendy

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metaboprep: an R package for preanalysis data description and processing

Author(s) -

David A. Hughes,

Kurt Taylor,

Nancy McBride,

Matthew A. Lee,

Dan Mason,

Debbie A. Lawlor,

Nicholas J. Timpson,

Laura J. Corbin

Publication year - 2022

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btac059

Subject(s) - computer science , workflow , preprocessor , standardization , data pre processing , context (archaeology) , data mining , r package , flexibility (engineering) , data quality , data processing , quality (philosophy) , open source , data science , set (abstract data type) , consistency (knowledge bases) , software , database , artificial intelligence , metric (unit) , programming language , paleontology , philosophy , statistics , operations management , mathematics , computational science , epistemology , biology , economics , operating system

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.

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