Depending on the type of experiments, there may be significant amount of missing values present in the data set.
Missing values should be presented either as empty values or NA without quotes in order to be accepted by MetaboAnalyst. Any other symbol will be treated as string character and could cause errors during data processing. MetaboAnalyst offers a variety of methods to deal with missing values.
- Remove features with a high-level (adjustable) missing values
- Fill the remaining NAs using detection limits (LoD) – 1/5 of the lowest positive values reported for individual features
- Users can also specify other methods, such as replace by mean/median, Probabilistic PCA (PPCA), Bayesian PCA (BPCA) method, or Singular Value Decomposition (SVD) method to impute the missing values (Stacklies W. et al).