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Here, we introduce the Spatial Omics Toolkit (SPOT), an end-to-end, open-source analytical pipeline that operationalizes established statistical methods from single-cell and spatial transcriptomics into accessible workflows for MSI data. SPOT is implemented in both R and Python, uses vendor-neutral community data formats, and integrates classification modeling, dimensionality reduction, and trajectory inference to enable spatially resolved comparative analysis across disease states with minimal computational overhead. We demonstrate the utility of SPOT on stromal proteomic profiles derived from ductal carcinoma in situ (DCIS) lesion archetypes, identifying differentially expressed peptides across disease states by orthogonal statistical approaches, and reconstructing a pseudotime trajectory from DCIS to invasive breast cancer from the same patient genetics. Collectively, SPOT provides researchers with a framework for interrogating molecular pathology across diverse MSI data sets. SPOT can be found at https:\/\/github.com\/angel-omics-lab.<\/jats:p>","DOI":"10.1021\/jasms.6c00183","type":"journal-article","created":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T12:20:46Z","timestamp":1788351646000},"page":"2628-2637","source":"Crossref","is-referenced-by-count":0,"title":["A Protocol for Multivariate\nData Visualization and\nPseudotime Modeling for Analysis of Disease Trajectories Detected\nby Mass Spectrometry Imaging"],"prefix":"10.1021","volume":"37","author":[{"given":"Bryn","family":"Gerding","sequence":"first","affiliation":[{"name":"Medical University of South Carolina , , , ,","place":["Charleston, South Carolina, United States, 29425"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Taylor","family":"Hulahan","sequence":"additional","affiliation":[{"name":"Medical University of South Carolina , , , ,","place":["Charleston, South Carolina, United States, 29425"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura","family":"Spruill","sequence":"additional","affiliation":[{"name":"Medical University of South Carolina , , , ,","place":["Charleston, South Carolina, United States, 29425"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harrison B.","family":"Taylor","sequence":"additional","affiliation":[{"name":"Medical University of South Carolina , , , ,","place":["Charleston, South Carolina, United States, 29425"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9846-9389","authenticated-orcid":true,"given":"Anand S.","family":"Mehta","sequence":"additional","affiliation":[{"name":"Medical University of South Carolina , , , ,","place":["Charleston, South Carolina, United States, 29425"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard R.","family":"Drake","sequence":"additional","affiliation":[{"name":"Medical University of South Carolina , , , ,","place":["Charleston, South Carolina, United States, 29425"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4436-555X","authenticated-orcid":true,"given":"Peggi M.","family":"Angel","sequence":"additional","affiliation":[{"name":"Medical University of South Carolina , , , ,","place":["Charleston, South Carolina, United States, 29425"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3268-610X","authenticated-orcid":true,"given":"Souvik","family":"Seal","sequence":"additional","affiliation":[{"name":"Medical University of South Carolina , , , ,","place":["Charleston, South Carolina, United States, 29425"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,8,29]]},"reference":[{"issue":"1","key":"2026100710063258100_cit1b","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1186\/s13059-017-1382-0","article-title":"SCANPY: large-scale single-cell gene\nexpression data analysis","volume":"19","author":"Wolf","year":"2018","journal-title":"Genome biology"},{"key":"2026100710063258100_cit1a","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1802.03426","article-title":"Umap: Uniform manifold approximation\nand projection for dimension reduction","author":"McInnes","year":"2018","journal-title":"arXiv:1802.03426"},{"issue":"6","key":"2026100710063258100_cit2","doi-asserted-by":"publisher","first-page":"1166","DOI":"10.1007\/s13361-016-1570-2","article-title":"Detection\nof metastatic\nbreast and thyroid cancer in lymph nodes by desorption electrospray\nionization mass spectrometry imaging","volume":"28","author":"Zhang","year":"2017","journal-title":"J. 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Mass Spectrom."},{"issue":"16","key":"2026100710063258100_cit3","doi-asserted-by":"publisher","first-page":"6180","DOI":"10.1021\/acs.analchem.1c05238","article-title":"\u2018On\nthe spot\u2019digital\npathology of breast cancer based on single-cell mass spectrometry\nimaging","volume":"94","author":"Cuypers","year":"2022","journal-title":"Analytical chemistry"},{"issue":"2","key":"2026100710063258100_cit4","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1016\/j.cell.2021.12.023","article-title":"Transition to invasive\nbreast cancer is associated with progressive changes in the structure\nand composition of tumor stroma","volume":"185","author":"Risom","year":"2022","journal-title":"Cell"},{"issue":"12","key":"2026100710063258100_cit5","doi-asserted-by":"publisher","first-page":"1521","DOI":"10.1016\/j.ccell.2022.10.021","article-title":"Molecular classification and biomarkers\nof clinical\noutcome in breast ductal carcinoma in situ: Analysis of TBCRC 038\nand RAHBT 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Genet."},{"issue":"5","key":"2026100710063258100_cit24","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1038\/s41587-019-0071-9","article-title":"A comparison\nof single-cell\ntrajectory inference methods","volume":"37","author":"Saelens","year":"2019","journal-title":"Nature biotechnology"},{"issue":"1","key":"2026100710063258100_cit25","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1186\/s12864-018-4772-0","article-title":"Slingshot: cell lineage\nand pseudotime inference for single-cell transcriptomics","volume":"19","author":"Street","year":"2018","journal-title":"BMC genomics"},{"issue":"13","key":"2026100710063258100_cit26","doi-asserted-by":"publisher","first-page":"e117","DOI":"10.1093\/nar\/gkw430","article-title":"TSCAN: Pseudo-time reconstruction and evaluation in\nsingle-cell RNA-seq\nanalysis","volume":"44","author":"Ji","year":"2016","journal-title":"Nucleic Acids Res."},{"issue":"12","key":"2026100710063258100_cit27","doi-asserted-by":"publisher","first-page":"1482","DOI":"10.1038\/s41587-019-0336-3","article-title":"Visualizing structure and transitions in high-dimensional\nbiological data","volume":"37","author":"Moon","year":"2019","journal-title":"Nature biotechnology"},{"key":"2026100710063258100_cit28","unstructured":"Trapnell, C.; Cacchiarelli, D.; Qiu, X.\n          Monocle: Cell counting,\ndifferential expression, and trajectory analysis for single-cell RNA-Seq\nexperiments; Bioconductor, https:\/\/www.bioconductor.org\/packages\/release\/bioc\/html\/monocle.html2017."},{"issue":"1","key":"2026100710063258100_cit29","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1186\/s12864-018-4772-0","article-title":"Slingshot:\ncell lineage\nand pseudotime inference for single-cell transcriptomics","volume":"19","author":"Street","year":"2018","journal-title":"BMC genomics"},{"issue":"1","key":"2026100710063258100_cit30","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1186\/s13058-024-01885-8","article-title":"Analysis of ductal carcinoma in situ\nby self-reported race reveals molecular differences related to outcome","volume":"26","author":"Strand","year":"2024","journal-title":"Breast Cancer Research"}],"container-title":["Journal of the American\nSociety for Mass Spectrometry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/jasms.6c00183","content-type":"application\/pdf","content-version":"vor","intended-application":"unspecified"},{"URL":"https:\/\/pubs.acs.org\/jamsef\/article-pdf\/37\/10\/2628\/67739677\/jasms.6c00183.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/pubs.acs.org\/jamsef\/article-pdf\/37\/10\/2628\/67739677\/jasms.6c00183.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T14:49:41Z","timestamp":1791384581000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/jamsef\/article\/37\/10\/2628\/5361419\/A-Protocol-for-Multivariate-Data-Visualization-and"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,29]]},"references-count":37,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2026,8,29]]},"published-print":{"date-parts":[[2026,10,7]]}},"URL":"https:\/\/doi.org\/10.1021\/jasms.6c00183","relation":{},"ISSN":["1044-0305","1879-1123"],"issn-type":[{"value":"1044-0305","type":"print"},{"value":"1879-1123","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,29]]}}}