Quantitative features of the proteome are extremely useful for studying cellular processes at a molecular level. In this study, we attempted to construct quantitative reference proteome maps of the mouse spleen and lymph node based on 2-DE followed by protein identification using MS. We analyzed more than 1000 spots on the 2-DE images and consequently were able to determine that 919 spots were derived from 328 different genes. To obtain statistically reliable information of the protein levels from these 2-DE images, we measured the volumes of the respective spots on 2-DE images obtained by four to six independent experimental runs. These measurements were used to calculate the variability of the volumes of the respective spots on 2-DE following subcellular fractionation, which enabled us to discriminate differentially produced proteins from those within the range of intrinsic variability. More importantly, while the 2-DE data have been traditionally collected in a gel image-based manner, the resultant quantitative 2-DE data could be analyzed using the same procedure as that for mRNA expression profiles. This greatly assists in bridging the gap between the analyses of transcriptomes and proteomes and enables the integration of this data on the same informational platform.