However, the quantification step is significantly different including multiple steps such as feature detection, normalization, and alignment . One of the main challenges in label-free based experiments is the high number of missing values across samples and replicates, which makes other steps like protein expression normalization difficult 16, 17 . In addition to the need to apply statistical tests, and perform the differential expression analysis, the high number of missing values presented in LFQ-based experiments has triggered the development of a variety of R-packages and algorithms that enable the statistical analysis of these datasets.