Sven Dorkenwald, Casey M Schneider-Mizell, Derrick Brittain, Akhilesh Halageri, Chris Jordan, Nico Kemnitz, Manual A Castro, William Silversmith, Jeremy Maitin-Shephard, Jakob Troidl, Hanspeter Pfister, Valentin Gillet, Daniel Xenes, J Alexander Bae, Agnes L Bodor, JoAnn Buchanan, Daniel J Bumbarger, Leila Elabbady, Zhen Jia, Daniel Kapner, Sam Kinn, Kisuk Lee, Kai Li, Ran Lu, Thomas Macrina, Gayathri Mahalingam, Eric Mitchell, Shanka Subhra Mondal, Shang Mu, Barak Nehoran, Sergiy Popovych, Marc Takeno, Russel Torres, Nicholas L Turner, William Wong, Jingpeng Wu, Wenjing Yin, Szi-Chieh Yu, R Clay Reid, Nuno Maçarico da Costa, H Sebastian Seung, Forrest Collman
{"title":"CAVE:连接体注释版本引擎。","authors":"Sven Dorkenwald, Casey M Schneider-Mizell, Derrick Brittain, Akhilesh Halageri, Chris Jordan, Nico Kemnitz, Manual A Castro, William Silversmith, Jeremy Maitin-Shephard, Jakob Troidl, Hanspeter Pfister, Valentin Gillet, Daniel Xenes, J Alexander Bae, Agnes L Bodor, JoAnn Buchanan, Daniel J Bumbarger, Leila Elabbady, Zhen Jia, Daniel Kapner, Sam Kinn, Kisuk Lee, Kai Li, Ran Lu, Thomas Macrina, Gayathri Mahalingam, Eric Mitchell, Shanka Subhra Mondal, Shang Mu, Barak Nehoran, Sergiy Popovych, Marc Takeno, Russel Torres, Nicholas L Turner, William Wong, Jingpeng Wu, Wenjing Yin, Szi-Chieh Yu, R Clay Reid, Nuno Maçarico da Costa, H Sebastian Seung, Forrest Collman","doi":"10.1038/s41592-024-02426-z","DOIUrl":null,"url":null,"abstract":"<p><p>Advances in electron microscopy, image segmentation and computational infrastructure have given rise to large-scale and richly annotated connectomic datasets, which are increasingly shared across communities. To enable collaboration, users need to be able to concurrently create annotations and correct errors in the automated segmentation by proofreading. In large datasets, every proofreading edit relabels cell identities of millions of voxels and thousands of annotations like synapses. For analysis, users require immediate and reproducible access to this changing and expanding data landscape. Here we present the Connectome Annotation Versioning Engine (CAVE), a computational infrastructure that provides scalable solutions for proofreading and flexible annotation support for fast analysis queries at arbitrary time points. Deployed as a suite of web services, CAVE empowers distributed communities to perform reproducible connectome analysis in up to petascale datasets (~1 mm<sup>3</sup>) while proofreading and annotating is ongoing.</p>","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"22 5","pages":"1112-1120"},"PeriodicalIF":36.1000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12074985/pdf/","citationCount":"0","resultStr":"{\"title\":\"CAVE: Connectome Annotation Versioning Engine.\",\"authors\":\"Sven Dorkenwald, Casey M Schneider-Mizell, Derrick Brittain, Akhilesh Halageri, Chris Jordan, Nico Kemnitz, Manual A Castro, William Silversmith, Jeremy Maitin-Shephard, Jakob Troidl, Hanspeter Pfister, Valentin Gillet, Daniel Xenes, J Alexander Bae, Agnes L Bodor, JoAnn Buchanan, Daniel J Bumbarger, Leila Elabbady, Zhen Jia, Daniel Kapner, Sam Kinn, Kisuk Lee, Kai Li, Ran Lu, Thomas Macrina, Gayathri Mahalingam, Eric Mitchell, Shanka Subhra Mondal, Shang Mu, Barak Nehoran, Sergiy Popovych, Marc Takeno, Russel Torres, Nicholas L Turner, William Wong, Jingpeng Wu, Wenjing Yin, Szi-Chieh Yu, R Clay Reid, Nuno Maçarico da Costa, H Sebastian Seung, Forrest Collman\",\"doi\":\"10.1038/s41592-024-02426-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Advances in electron microscopy, image segmentation and computational infrastructure have given rise to large-scale and richly annotated connectomic datasets, which are increasingly shared across communities. To enable collaboration, users need to be able to concurrently create annotations and correct errors in the automated segmentation by proofreading. In large datasets, every proofreading edit relabels cell identities of millions of voxels and thousands of annotations like synapses. For analysis, users require immediate and reproducible access to this changing and expanding data landscape. Here we present the Connectome Annotation Versioning Engine (CAVE), a computational infrastructure that provides scalable solutions for proofreading and flexible annotation support for fast analysis queries at arbitrary time points. 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Advances in electron microscopy, image segmentation and computational infrastructure have given rise to large-scale and richly annotated connectomic datasets, which are increasingly shared across communities. To enable collaboration, users need to be able to concurrently create annotations and correct errors in the automated segmentation by proofreading. In large datasets, every proofreading edit relabels cell identities of millions of voxels and thousands of annotations like synapses. For analysis, users require immediate and reproducible access to this changing and expanding data landscape. Here we present the Connectome Annotation Versioning Engine (CAVE), a computational infrastructure that provides scalable solutions for proofreading and flexible annotation support for fast analysis queries at arbitrary time points. Deployed as a suite of web services, CAVE empowers distributed communities to perform reproducible connectome analysis in up to petascale datasets (~1 mm3) while proofreading and annotating is ongoing.
期刊介绍:
Nature Methods is a monthly journal that focuses on publishing innovative methods and substantial enhancements to fundamental life sciences research techniques. Geared towards a diverse, interdisciplinary readership of researchers in academia and industry engaged in laboratory work, the journal offers new tools for research and emphasizes the immediate practical significance of the featured work. It publishes primary research papers and reviews recent technical and methodological advancements, with a particular interest in primary methods papers relevant to the biological and biomedical sciences. This includes methods rooted in chemistry with practical applications for studying biological problems.