{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T21:30:58Z","timestamp":1775165458206,"version":"3.50.1"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"9","license":[{"start":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T00:00:00Z","timestamp":1694476800000},"content-version":"vor","delay-in-days":11,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Innovation and Technology Commission of Hong Kong"},{"name":"Australian Research Council Discovery Early Career Researcher","award":["DE220100964"],"award-info":[{"award-number":["DE220100964"]}]},{"name":"Australian Research Council Discovery Early Career Researcher","award":["DE200100944"],"award-info":[{"award-number":["DE200100944"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Imaging-based spatial transcriptomics (ST) technologies have achieved subcellular resolution, enabling detection of individual molecules in their native tissue context. Data associated with these technologies promise unprecedented opportunity toward understanding cellular and subcellular biology. However, in R\/Bioconductor, there is a scarcity of existing computational infrastructure to represent such data, and particularly to summarize and transform it for existing widely adopted computational tools in single-cell transcriptomics analysis, including SingleCellExperiment and SpatialExperiment (SPE) classes. With the emergence of several commercial offerings of imaging-based ST, there is a pressing need to develop consistent data structure standards for these technologies at the individual molecule-level.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>To this end, we have developed MoleculeExperiment, an R\/Bioconductor package, which (i) stores molecule and cell segmentation boundary information at the molecule-level, (ii) standardizes this molecule-level information across different imaging-based ST technologies, including 10\u00d7 Genomics\u2019 Xenium, and (iii) streamlines transition from a MoleculeExperiment object to a SpatialExperiment object. Overall, MoleculeExperiment is generally applicable as a data infrastructure class for consistent analysis of molecule-resolved spatial omics data.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The MoleculeExperiment package is publicly available on Bioconductor at https:\/\/bioconductor.org\/packages\/release\/bioc\/html\/MoleculeExperiment.html. Source code is available on Github at: https:\/\/github.com\/SydneyBioX\/MoleculeExperiment. The vignette for MoleculeExperiment can be found at https:\/\/bioconductor.org\/packages\/release\/bioc\/html\/MoleculeExperiment.html.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btad550","type":"journal-article","created":{"date-parts":[[2023,9,11]],"date-time":"2023-09-11T12:23:00Z","timestamp":1694434980000},"source":"Crossref","is-referenced-by-count":12,"title":["<i>MoleculeExperiment<\/i> enables consistent infrastructure for molecule-resolved spatial omics data in bioconductor"],"prefix":"10.1093","volume":"39","author":[{"given":"B\u00e1rbara Zita","family":"Peters Couto","sequence":"first","affiliation":[{"name":"School of Mathematics and Statistics, The University of Sydney , Camperdown, NSW 2006, Australia"},{"name":"Charles Perkins Centre, The University of Sydney , Camperdown, NSW 2006, Australia"},{"name":"Sydney Precision Data Science Centre, The University of Sydney , Camperdown, NSW 2006, Australia"}]},{"given":"Nicholas","family":"Robertson","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, The University of Sydney , Camperdown, NSW 2006, Australia"},{"name":"Charles Perkins Centre, The University of Sydney , Camperdown, NSW 2006, Australia"},{"name":"Sydney Precision Data Science Centre, The University of Sydney , Camperdown, NSW 2006, Australia"},{"name":"Sydney Laboratory of Data Discovery for Health Limited (D24H), Science Park , Hong Kong SAR, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5253-4747","authenticated-orcid":false,"given":"Ellis","family":"Patrick","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, The University of Sydney , Camperdown, NSW 2006, Australia"},{"name":"Charles Perkins Centre, The University of Sydney , Camperdown, NSW 2006, Australia"},{"name":"Sydney Precision Data Science Centre, The University of Sydney , Camperdown, NSW 2006, Australia"},{"name":"Sydney Laboratory of Data Discovery for Health Limited (D24H), Science Park , Hong Kong SAR, China"},{"name":"Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney , Westmead, NSW 2145, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7861-6997","authenticated-orcid":false,"given":"Shila","family":"Ghazanfar","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, The University of Sydney , Camperdown, NSW 2006, Australia"},{"name":"Charles Perkins Centre, The University of Sydney , Camperdown, NSW 2006, Australia"},{"name":"Sydney Precision Data Science Centre, The University of Sydney , Camperdown, NSW 2006, Australia"}]}],"member":"286","published-online":{"date-parts":[[2023,9,12]]},"reference":[{"key":"2023092719500414900_btad550-B1","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1038\/s41592-019-0654-x","article-title":"Orchestrating single-cell analysis with 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