The genome serves as a blueprint for organisms, encompassing genetic instructions for their growth and development. Advancements in genomics and proteomics techniques have provided unprecedented insights into their genetic makeup and how these instructions are translated into functional proteins. Proteogenomics has emerged as a powerful technique which generates sample-specific proteome databases based on in silico prediction of translated proteins. RNA-seq driven proteogenomics provides distinct advantages to precisely map sample-specific gene expression and characterize proteoforms with high sensitivity. Several bioinformatics workflows have been developed to generate custom proteogenomic databases. However, they are not user friendly as they lack Graphical User Interphase and require programming expertise for execution. Furthermore, current packages do not annotate open reading frames (ORFs) across reference genomes/transcriptomes, or proteomes from UniProt/OpenProt making it challenging to perform downstream analysis. Moreover, these approaches rely on short-read RNA-Seq data, which is prone to ambiguous transcript assembly. To address these limitations, we have developed a GUI based tool which enables users to upload long-read RNA-Seq data and generate sample-specific annotated proteome database (.fasta) tailored for downstream proteomics analysis. Furthermore, we develop and novel workflow for the visualisation and mapping of peptide annotation on the genome. We demonstrate the use of this tool by performing deep multi-protease proteomics on the Orbitrap Astral, and paired Oxford Nanopore long-read RNAseq of mouse/human cell lines, a mouse model of melanoma tissue, and analysis of different brain regions from human donors. Our results allow for the discovery of: i) novel proteoforms arising from alternative spicing/initiation/termination, ii) microproteins from previously annotated untranslated regions of ORFs, iii) novel proteins identified from lncRNA, and iv) validation of missense single nucleotide polymorphisms. We expect GenomeProt to make proteogenomics more accessible to the community and will be applicable to a range of applications including precision medicine and annotation of the genome.