The detection of physiologically relevant protein isoforms encoded by the human genome is critical to biomedicine. Mass spectrometry (MS)-based proteomics is the preeminent method for protein detection, but isoform-resolved proteomic analysis relies on accurate reference databases that match the sample; neither a subset nor a superset database is ideal. Long-read RNA sequencing (e.g. PacBio, Oxford Nanopore) provide full-length transcript sequencing, which can be used to predict full-length proteins. Here, we describe a long-read proteogenomics approach for integrating matched long-read RNA-seq and MS-based proteomics data to enhance isoform characterization. We introduce a classification scheme for protein isoforms, discovery novel protein isoforms, and present the first protein inference algorithm for the direct incorporation of long-read transcriptome data in protein inference to enable detection of protein isoforms that are intractable to MS detection. We have released an open-source Nextflow pipeline that integrates long-read RNA-sequencing in a proteomic workflow for isoform-resolved analysis. Companion Repositories: Long-Read-Proteogenomics Workflow GitHub Repository Release Long-Read-Proteogenomics Analysis GitHub Repository Release Companion Datasets TEST Data for Long-Read-Proteogenomics Workflow GitHub Actions Long-Read-Proteogenomics Workflow Results using Jurkat Sample data This Repository contains the Jurkat Samples and Reference Data