Update publication information. Phosphoproteomics and ubiquitinomics data-independent acquisition MS data is generally analyzed using a DDA spectral library. Performance of different library-free strategies of analyzing phosphoproteomics and ubiquitinomics DIA MS data are not evaluated. In this study, we assess three library-free approaches including DIA-Umpire, DIA-MSFragger and in silico-predicted library for analysis of phosphoproteomics SWATH, DIA and diaPASEF data as well as ubiquitinomics diaPASEF data. In silico-predicted library based on DIA-NN performs best among three library-free methods, but identify less or equal phosphopeptides compared to a DDA spectral library. Furthermore, the common phosphopeptides by the predicted library and DDA library are about 50%. This case is also observed for phospho-diaPASEF data. For ubiquitinomics diaPASEF data, in silico-predicted library detects about 50% more K-GG peptides than a project-specific DDA spectral library. Our results demonstrate that the predicted library, although performs best in library-free methods, requires improvement for phospho DIA MS data and displays substantial advantages for ubiquitinomics diaPASEF MS data.