Since Venable et al. first introduced data-independent acquisition (DIA) in 2004, DIA acquisition and data analysis tools have been continuously improved, making DIA a vital technology to identify and quantify thousands of proteins with high reproducibility and deep proteomics coverage. DIA data analysis, in general, relies on a spectral library constructed from data-dependent acquisition (DDA). Alternatively, the library-free approach searches DIA data directly against a fasta database. We combined a recently developed CCS-aware ProLuCID-4D search engine using ion mobility and a spectral library-based DIA approach to increase coverage.