Label-free quantitative approach based mass spectrometry was used for analysis of complex proteomes, meanwhile, a method based on quantitative analysis which is used for explaining functions and interactions in a large-scale manner is of great importance. To systematically overcome this challenge, we should build a method combing with quantitation and qualification. We used Normalized Spectral Abundance Factor (NSAF) based peptide count as starting point for our analysis and proposed a new method with shared peptides to accurately evaluate abundance of Isoforms for complex proteomes. In addition, large-scale functional annotations of complex proteomes were extracted by g:Profiler and analyzed in the process of quantitation. In this paper, three groups of mitochondrial proteins including mouse heart mitochondrial proteins, mouse liver mitochondrial proteins and human heart mitochondrial proteins were selected for analysis. All MS/MS spectra t were searched against the IPI mouse database and IPI human database using the pFind software kit. Detailed search parameters were performed using as follows: partial tryptic digest allowing two missed cleavages; fixed modification of cysteine with carbamidomethylation (57.021 Da) and variable modification of methionine with oxidation (15.995 Da), the precursor and fragment mass tolerances were set up at 1.5 and 0.5 Da, respectively. Peptides matching the following criteria were used for protein identification: DeltaCN≥0.1; FDR≤1.0%; peptide mass was 600.0～6000.0; peptide length was 6～60. According to the biochemical properties of mitochondrial proteins, all functional annotations were assigned to various signaling pathway or functional clusters, such as apoptosis, DNA/RNA/protein synthesis, metabolism, oxidative phosphorylation, protein binding/folding, proteolysis, redox, signal transduction, structure, transport, cell adhesion and cell cycle, and analyzed by correlation analysis, functional clustering and electron transport chain analysis. We found that proteins which rank have enormous variation between NSAF and the new method even came from a same family, such as proteins belonging to acyl-CoA dehydrogenase family. Proteins in the family play an important role in life event due to their biochemical properties of fatty acid metabolism and lipid metabolism searched using the online database analysis tool available through UniProt (www.uniprot.org). From the global perspective of the three groups of mitochondrial proteins, the correlation of mouse heart mitochondrial proteins and mouse liver mitochondrial proteins shows highest, while the correlation of human heart mitochondrial proteins and mouse liver mitochondrial proteins shows lowest, it denotes that the correlation of simple species and different organs shows highest. On the aspect of functional clustering, metabolic proteins have highest abundance in mouse liver mitochondrial dataset, while oxidative phosphorylation proteins show highest abundance in cardiac mitochondrial dataset. This explains that liver plays an important role in metabolic process including nutrients synthesis, transformation and decomposition, however, heart promotes blood flowing to provide adequate blood to the organs or tissues, supply oxygen or various nutrients and take metabolic products away. We concluded that the strategy with shared peptides overcame inaccurate and overestimated results to improve accuracy, and label-free quantitative approach coupled with complex proteome functional analysis can thoroughly explore protein functions or relationship and provide a new method for large-scale comparative or diseased proteomics.