{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Weaver SD"],"funding":["National Institutes of Health","NIGMS NIH HHS"],"pagination":["432-441"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9904286"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["22(2)"],"pubmed_abstract":["Bottom-up proteomics (BUP) produces rich data, but visualization and analysis are time-consuming and often require programming skills. Many tools analyze these data at the proteome-level, but fewer options exist for individual proteins. Sequence coverage maps are common, but do not proportion peptide intensity. Abundance-based visualization of sequence coverage facilitates detection of protein isoforms, domains, potential truncation sites, peptide \"hot-spots\", and localization of post-translational modifications (PTMs). Redundant stacked-sequence coverage is an important tool in designing hydrogen-deuterium exchange (HDX) experiments. Visualization tools often lack graphical and tabular-export of processed data which complicates publication of results. Quantitative peptide abundance across amino acid sequences is an essential and missing tool in proteomics toolkits. Here we created PrIntMap-R, an online application that only requires peptide files from a database search and FASTA protein sequences. PrIntMap-R produces a variety of plots for quantitative visualization of coverage; annotation of specific sequences, PTM's, and comparisons of one or many samples overlaid with calculated fold-change or several intensity metrics. We show use-cases including protein phosphorylation, identification of glycosylation, and the optimization of digestion conditions for HDX experiments. PrIntMap-R is freely available, open source, and can run online with no installation, or locally by downloading source code from GitHub."],"journal":["Journal of proteome research"],"pubmed_title":["PrIntMap-R: An Online Application for Intraprotein Intensity and Peptide Visualization from Bottom-Up Proteomics."],"pmcid":["PMC9904286"],"funding_grant_id":["R01 GM139277","T32 GM075762","T32GM075762","R01GM139277"],"pubmed_authors":["DeRosa CM","Champion MM","Weaver SD","Schultz SR"],"additional_accession":[]},"is_claimable":false,"name":"PrIntMap-R: An Online Application for Intraprotein Intensity and Peptide Visualization from Bottom-Up Proteomics.","description":"Bottom-up proteomics (BUP) produces rich data, but visualization and analysis are time-consuming and often require programming skills. Many tools analyze these data at the proteome-level, but fewer options exist for individual proteins. Sequence coverage maps are common, but do not proportion peptide intensity. Abundance-based visualization of sequence coverage facilitates detection of protein isoforms, domains, potential truncation sites, peptide \"hot-spots\", and localization of post-translational modifications (PTMs). Redundant stacked-sequence coverage is an important tool in designing hydrogen-deuterium exchange (HDX) experiments. Visualization tools often lack graphical and tabular-export of processed data which complicates publication of results. Quantitative peptide abundance across amino acid sequences is an essential and missing tool in proteomics toolkits. Here we created PrIntMap-R, an online application that only requires peptide files from a database search and FASTA protein sequences. PrIntMap-R produces a variety of plots for quantitative visualization of coverage; annotation of specific sequences, PTM's, and comparisons of one or many samples overlaid with calculated fold-change or several intensity metrics. We show use-cases including protein phosphorylation, identification of glycosylation, and the optimization of digestion conditions for HDX experiments. PrIntMap-R is freely available, open source, and can run online with no installation, or locally by downloading source code from GitHub.","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Feb","modification":"2026-06-26T03:12:00.84Z","creation":"2025-04-04T09:53:22.55Z"},"accession":"S-EPMC9904286","cross_references":{"pubmed":["36652611"],"doi":["10.1021/acs.jproteome.2c00606"]}}