Proteogenomics includes the transfer of knowledge from proteomics to genomics and vice versa. To have high confidence in the information transferred it is essential that it be based on experimental results. Genomics is currently fueled by high throughput techniques involving next generation sequencing. Proteomics is based on mass spectrometry (MS) which is also a high throughput approach. Both fields are generating a wealth of data which needs to be correlated and annotated to generate knowledge. Publicly available human blood plasma mass spectrometric data exist for samples in data repositories such as PeptideAtlas, PRIDE. We acquired high-quality collections from this data and stored it in a custom database developed by us. First, we aimed to amend this data by employing a proteogenomic pipeline PGMiner developed in this study against a custom sequence database which includes all predicted alternative open reading frames as well as the six-frame translation of the human genome and exosome. Then, we correlated the existing annotations with the available mass spectrometric measurements. The human genome in tandem with currently available genome annotations from HAVANA and ENSEMBL enabled us to validate and enhance current gene annotations.