{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,1,28]],"date-time":"2023-01-28T05:22:37Z","timestamp":1674883357751},"reference-count":8,"publisher":"Oxford University Press (OUP)","issue":"18","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,9,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary : Current data formats for the representation of depth of coverage data (DOC), a central resource for interpreting, filtering or detecting novel features in high-throughput sequencing datasets, were primarily designed for visualization purposes. This limits their applicability in stand-alone analyses of these data, mainly owing to inaccurate representation or mediocre data compression. CODOC is a novel data format and comprehensive application programming interface for efficient representation, access and analysis of DOC data. CODOC compresses these data \u223c4\u201332\u00d7 better than the best current comparable method by exploiting specific data characteristics while at the same time enabling more-exact signal recovery for lossy compression and very fast query answering times.<\/jats:p>\n               <jats:p>Availability and implementation: Java source code and binaries are freely available for non-commercial use at http:\/\/purl.org\/bgraph\/codoc .<\/jats:p>\n               <jats:p>Contact: \u00a0niko.popitsch@univie.ac.at<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data and usage examples are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btu362","type":"journal-article","created":{"date-parts":[[2014,5,29]],"date-time":"2014-05-29T03:33:46Z","timestamp":1401334426000},"page":"2676-2677","source":"Crossref","is-referenced-by-count":3,"title":["CODOC: efficient access, analysis and compression of depth of coverage signals"],"prefix":"10.1093","volume":"30","author":[{"given":"Niko","family":"Popitsch","sequence":"first","affiliation":[{"name":"Center for Integrative Bioinformatics Vienna (CIBIV), Max F Perutz Laboratories, University of Vienna and Medical University of Vienna, Dr. Bohrgasse 9, 1030 Vienna, Austria"}]}],"member":"286","published-online":{"date-parts":[[2014,5,28]]},"reference":[{"key":"2023012711552663600_btu362-B1","doi-asserted-by":"crossref","first-page":"1435","DOI":"10.1038\/nsmb.2143","article-title":"Total rna sequencing reveals nascent transcription and widespread co-transcriptional splicing in the human brain","volume":"18","author":"Ameur","year":"2011","journal-title":"Nat. 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