Multiple Imputation Approaches Applied to the Missing Value Problem in Bottom-Up Proteomics.
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ABSTRACT:
SUBMITTER: Gardner ML
PROVIDER: S-EPMC8431783 | biostudies-literature | 2021 Sep
REPOSITORIES: biostudies-literature
Publications
Multiple Imputation Approaches Applied to the Missing Value Problem in Bottom-Up Proteomics.
Gardner Miranda L ML Freitas Michael A MA
International journal of molecular sciences 20210906 17
Analysis of differential abundance in proteomics data sets requires careful application of missing value imputation. Missing abundance values widely vary when performing comparisons across different sample treatments. For example, one would expect a consistent rate of "missing at random" (MAR) across batches of samples and varying rates of "missing not at random" (MNAR) depending on the inherent difference in sample treatments within the study. The missing value imputation strategy must thus be ...[more]
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