Influence of Missing Values Substitutes on Multivariate Analysis of Metabolomics Data
Missing values are known to be problematic for the analysis of gas chromatography-mass spectrometry (GC-MS) metabolomics data. Typically these values cover about 10%–20% of all data and can originate from various backgrounds, including analytical, computational, as well as biological. Currently, the...
| Main Authors: | , , , , , , , |
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| Format: | Online |
| Language: | English |
| Published: |
MDPI
2014
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4101515/ |