{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T02:07:31Z","timestamp":1762999651897,"version":"3.37.3"},"reference-count":11,"publisher":"Oxford University Press (OUP)","issue":"18","license":[{"start":{"date-parts":[[2021,3,14]],"date-time":"2021-03-14T00:00:00Z","timestamp":1615680000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000092","name":"National Library of Medicine","doi-asserted-by":"publisher","award":["R01LM013154-01"],"award-info":[{"award-number":["R01LM013154-01"]}],"id":[{"id":"10.13039\/100000092","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Informatics Technology for Cancer Research","award":["1U01 CA220413-01"],"award-info":[{"award-number":["1U01 CA220413-01"]}]},{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,9,29]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>R Experiment objects such as the SummarizedExperiment or SingleCellExperiment are data containers for storing one or more matrix-like assays along with associated row and column data. These objects have been used to facilitate the storage and analysis of high-throughput genomic data generated from technologies such as single-cell RNA sequencing. One common computational task in many genomics analysis workflows is to perform subsetting of the data matrix before applying down-stream analytical methods. For example, one may need to subset the columns of the assay matrix to exclude poor-quality samples or subset the rows of the matrix to select the most variable features. Traditionally, a second object is created that contains the desired subset of assay from the original object. However, this approach is inefficient as it requires the creation of an additional object containing a copy of the original assay and leads to challenges with data provenance.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>To overcome these challenges, we developed an R package called ExperimentSubset, which is a data container that implements classes for efficient storage and streamlined retrieval of assays that have been subsetted by rows and\/or columns. These classes are able to inherently provide data provenance by maintaining the relationship between the subsetted and parent assays. We demonstrate the utility of this package on a single-cell RNA-seq dataset by storing and retrieving subsets at different stages of the analysis while maintaining a lower memory footprint. Overall, the ExperimentSubset is a flexible container for the efficient management of subsets.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>ExperimentSubset package is available at Bioconductor: https:\/\/bioconductor.org\/packages\/ExperimentSubset\/ and Github: https:\/\/github.com\/campbio\/ExperimentSubset.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab179","type":"journal-article","created":{"date-parts":[[2021,3,12]],"date-time":"2021-03-12T20:11:24Z","timestamp":1615579884000},"page":"3058-3060","source":"Crossref","is-referenced-by-count":8,"title":["ExperimentSubset: an R package to manage subsets of Bioconductor Experiment objects"],"prefix":"10.1093","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8121-792X","authenticated-orcid":false,"given":"Irzam","family":"Sarfraz","sequence":"first","affiliation":[{"name":"Department of Computer Science, National Textile University , Faisalabad 37610, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1839-2527","authenticated-orcid":false,"given":"Muhammad","family":"Asif","sequence":"additional","affiliation":[{"name":"Department of Computer Science, National Textile University , Faisalabad 37610, Pakistan"}]},{"given":"Joshua D","family":"Campbell","sequence":"additional","affiliation":[{"name":"Department of Medicine, Boston University School of Medicine , Boston, MA 02118, USA"}]}],"member":"286","published-online":{"date-parts":[[2021,3,14]]},"reference":[{"year":"2020","author":"Hansen","key":"2023061310561883400_btab179-B1"},{"key":"2023061310561883400_btab179-B2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13073-017-0467-4","article-title":"A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications","volume":"9","author":"Haque","year":"2017","journal-title":"Genome Med"},{"key":"2023061310561883400_btab179-B3","doi-asserted-by":"crossref","first-page":"1246","DOI":"10.12688\/f1000research.26669.2","article-title":"TreeSummarizedExperiment: a S4 class for data with hierarchical structure","volume":"9","author":"Huang","year":"2021","journal-title":"F1000Research"},{"key":"2023061310561883400_btab179-B4","doi-asserted-by":"crossref","first-page":"1543","DOI":"10.1101\/gr.121095.111","article-title":"Synthetic spike-in standards for RNA-seq experiments","volume":"21","author":"Jiang","year":"2011","journal-title":"Genome Res"},{"year":"2020","author":"Lun","key":"2023061310561883400_btab179-B5"},{"year":"2008","key":"2023061310561883400_btab179-B7"},{"key":"2023061310561883400_btab179-B8","doi-asserted-by":"crossref","first-page":"e39","DOI":"10.1158\/0008-5472.CAN-17-0344","article-title":"Software for the integration of multiomics experiments in bioconductor","volume":"77","author":"Ramos","year":"2017","journal-title":"Cancer Res"},{"key":"2023061310561883400_btab179-B9","doi-asserted-by":"crossref","first-page":"586","DOI":"10.1016\/j.molcel.2015.05.004","article-title":"High-throughput sequencing technologies","volume":"58","author":"Reuter","year":"2015","journal-title":"Mol. 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Bioinform"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btab179\/36651068\/btab179.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/37\/18\/3058\/50579308\/btab179.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/37\/18\/3058\/50579308\/btab179.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T10:58:13Z","timestamp":1686653893000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/37\/18\/3058\/6170656"}},"subtitle":[],"editor":[{"given":"Anthony","family":"Mathelier","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2021,3,14]]},"references-count":11,"journal-issue":{"issue":"18","published-print":{"date-parts":[[2021,9,29]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btab179","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"type":"print","value":"1367-4803"},{"type":"electronic","value":"1367-4811"}],"subject":[],"published-other":{"date-parts":[[2021,9,15]]},"published":{"date-parts":[[2021,3,14]]}}}