GFAP Degradome Foundation Atlas

GFAP Degradome Foundation Atlas Version 3: Extended Coverage of GFAP isoforms and mutationsThis open-access dataset presents the Version 3 of the Glial Fibrillary Acidic Protein (GFAP) Degradome Foundation Atlas, a comprehensive proteolytic peptide dataset designed to support translational research in neurodegenerative disease. This updated version (GFAP_Degradome_Foundation_Atlas_v3.tar.gz) integrates previous files into a single unified dataset at high compression level, improving usability and speed of free download.Version 3 expands on the earlier releases by incorporating proteolytic fragments associated with GFAP isoforms in addition to mutations associated with AxD. These data may prove particularly useful for clinical researchers designing or analyzing trials involving antisense oligonucleotides or biomarker-based outcome measures.Each peptide entry now features a revised nomenclature that encodes the mutation type, cleavage start and stop positions relative to the full-length GFAP sequence (e.g., "GFAP-D128N-125-130" for mutant, "GFAP-WT-125-130" for wild type, and "GFAP-kappa-21-42" for an isoform proteolytic fragment). This provides immediate interpretability and facilitates statistical analysis.The dataset is provided as a tab-delimited ASCII (.txt) file for straightforward compatibility with statistical and bioinformatics pipelines. Because of the expanded data volume and annotation depth, the file is compressed for efficiency. To extract you can use the bash terminal command: tar -xvJf GFAP_Degradome_Foundation_Atlas_v3.tar.gzCodesDataset generation is reproducible using three open-source tools:Python, BLAST, and SAS.Accompanying scripts are included in the repository and fully documented for transparency. Users are encouraged to adjust file paths and settings to their local environment. These scripts follow the methodology detailed in [1].References[1] Petzold A. Proteolysis-Based Biomarker Repertoire of the Neurofilament Proteome. J Neurochem. 2025 Mar;169(3):e70023.doi: 10.1111/jnc.70023. PMID: 40066701; PMCID: PMC11894590.