1-D and 2-D LC methods were utilized for proteome analysis of undepleted human serum. Separation of peptides in 2-D LC was performed either with strong cation exchange (SCX)-RP chromatography or with an RP-RP 2-D LC approach. Peptides were identified by MS/MS using a data-independent acquisition approach. A peptide retention prediction model was used to highlight the potential false-positive peptide identifications. When applying selected data filtration, we identified 52 proteins based on 316 peptides in serum in 1-D LC setup. One hundred and eighty-four proteins/1036 peptides and 142 proteins/905 peptides were identified in RP-RP and SCX-RP 2-D LC, respectively. The performance of both 2-D LC methods for proteomic analysis is critically compared.