I am not very clear about your questions here. Some quick comments
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You can analyze proteomics data using either ExpressAnalyst or MetaboAnalyst. However, there are some subtle differences: ExpressAnalyst follows Microarray/RNAseq practices. For instance, volcano plots and fold changes will be extracted from limma (microarray & proteomics), edgeR, DEseq outputs. MetaboAnalyst follows its own routine. It will directly use original values for FC analysis
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R command order indicates logical steps, but the program has access to multiple copies of the data at different stages (original, filtered, normlized). It can use original data even after normalization step.
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Should imputation be performed before or after normalization step? It depends. For instance, missing due to below the detection limits - they should be performed at original scale. In fact, many imputation methods will have its own built-in normlization procedures to ensure the performance (they will convert back to the original scale after imputation)