{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,6,22]],"date-time":"2024-06-22T20:10:11Z","timestamp":1719087011414},"reference-count":14,"publisher":"Oxford University Press (OUP)","issue":"13","license":[{"start":{"date-parts":[[2017,3,3]],"date-time":"2017-03-03T00:00:00Z","timestamp":1488499200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/about_us\/legal\/notices"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,7,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Summary<\/jats:title><jats:p>A pre-requisite to clustering noisy data, such as gene-expression data, is the filtering step. As an alternative to this step, the ctsGE R-package applies a sorting step in which all of the data are divided into small groups. The groups are divided according to how the time points are related to the time-series median. Then clustering is performed separately on each group. Thus, the clustering is done in two steps. First, an expression index (i.e. a sequence of 1, \u22121 and 0) is defined and genes with the same index are grouped together, and then each group of genes is clustered by k-means to create subgroups. The ctsGE package also provides an interactive tool to visualize and explore the gene-expression patterns and their subclusters. ctsGE proposes a way of organizing and exploring expression data without eliminating valuable information.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and Implementation<\/jats:title><jats:p>Freely available as part of the Bioconductor project at https:\/\/bioconductor.org\/packages\/ctsGE\/.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btx116","type":"journal-article","created":{"date-parts":[[2017,3,1]],"date-time":"2017-03-01T20:48:26Z","timestamp":1488401306000},"page":"2053-2055","source":"Crossref","is-referenced-by-count":2,"title":["ctsGE\u2014clustering subgroups of expression data"],"prefix":"10.1093","volume":"33","author":[{"given":"Michal","family":"Sharabi-Schwager","sequence":"first","affiliation":[{"name":"Department of Fruit Tree Sciences, Institute of Plant Sciences, Agricultural Research Organization, Volcani Center, Rishon Lezion, Israel"}]},{"given":"Etti","family":"Or","sequence":"additional","affiliation":[{"name":"Department of Fruit Tree Sciences, Institute of Plant Sciences, Agricultural Research Organization, Volcani Center, Rishon Lezion, Israel"}]},{"given":"Ron","family":"Ophir","sequence":"additional","affiliation":[{"name":"Department of Fruit Tree Sciences, Institute of Plant Sciences, Agricultural Research Organization, Volcani Center, Rishon Lezion, Israel"}]}],"member":"286","published-online":{"date-parts":[[2017,3,3]]},"reference":[{"key":"2023020206030680700_btx116-B1","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1038\/ng1031","article-title":"Fundamentals of experimental design for cDNA microarrays","volume":"32","author":"Churchill","year":"2002","journal-title":"Nat. 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