Ibaqpy parquet format output operations

[ypriverol]

Would be great to have a set of functions in the ibaqpy_postprocessing.py that performs the following operations:

• Remove samples with a percentage of missing values higher than X (e.g. 30%).
• Plot the boxplot similar to Figure 1, of a given quant variable (e.g. IbaqNorm) of the CVs and distributions of values. Would be good to have also the numbers, meaning standard deviation, etc. Additionally, the user should be able to use an extra variable (e.g. disease) to see the distributions.
• PCA and T-SNE to cluster all the samples.
• Imputation with KNNImputer, keep in mind that for the imputations the user should use similar Conditions or use other variables like disease or confounding variables.

Figure 1: Boxplot of IbaqNorm 👇