RCytoGPS: an R package for reading and visualizing cytogenetics data
Abstract Summary Cytogenetics data, or karyotypes, are among the most common clinically used forms of genetic data. Karyotypes are stored as standardized text strings using the International System for Human Cytogenomic Nomenclature (ISCN). Historically, these data have not been used in large-scale...
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| Veröffentlicht in: | Bioinformatics 2021-12, Vol.37 (23), p.4589-4590 |
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| container_title | Bioinformatics |
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| creator | Abrams, Zachary B Tally, Dwayne G Abruzzo, Lynne V Coombes, Kevin R |
| description | Abstract
Summary
Cytogenetics data, or karyotypes, are among the most common clinically used forms of genetic data. Karyotypes are stored as standardized text strings using the International System for Human Cytogenomic Nomenclature (ISCN). Historically, these data have not been used in large-scale computational analyses due to limitations in the ISCN text format and structure. Recently developed computational tools such as CytoGPS have enabled large-scale computational analyses of karyotypes. To further enable such analyses, we have now developed RCytoGPS, an R package that takes JSON files generated from CytoGPS.org and converts them into objects in R. This conversion facilitates the analysis and visualizations of karyotype data. In effect this tool streamlines the process of performing large-scale karyotype analyses, thus advancing the field of computational cytogenetic pathology.
Availability and implementation
Freely available at https://CRAN.R-project.org/package=RCytoGPS. The code for the underlying CytoGPS software can be found at https://github.com/i2-wustl/CytoGPS |
| doi_str_mv | 10.1093/bioinformatics/btab683 |
| format | Article |
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Summary
Cytogenetics data, or karyotypes, are among the most common clinically used forms of genetic data. Karyotypes are stored as standardized text strings using the International System for Human Cytogenomic Nomenclature (ISCN). Historically, these data have not been used in large-scale computational analyses due to limitations in the ISCN text format and structure. Recently developed computational tools such as CytoGPS have enabled large-scale computational analyses of karyotypes. To further enable such analyses, we have now developed RCytoGPS, an R package that takes JSON files generated from CytoGPS.org and converts them into objects in R. This conversion facilitates the analysis and visualizations of karyotype data. In effect this tool streamlines the process of performing large-scale karyotype analyses, thus advancing the field of computational cytogenetic pathology.
Availability and implementation
Freely available at https://CRAN.R-project.org/package=RCytoGPS. The code for the underlying CytoGPS software can be found at https://github.com/i2-wustl/CytoGPS</description><identifier>ISSN: 1367-4803</identifier><identifier>EISSN: 1460-2059</identifier><identifier>EISSN: 1367-4811</identifier><identifier>DOI: 10.1093/bioinformatics/btab683</identifier><identifier>PMID: 34601554</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Applications Notes ; Humans ; Karyotype ; Karyotyping ; Reading ; Software</subject><ispartof>Bioinformatics, 2021-12, Vol.37 (23), p.4589-4590</ispartof><rights>The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com 2021</rights><rights>The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c457t-b24d16bcb6f6ccab1a9fb47cc13f8bc8ec4ee5bd8b80c1868ce2a6a08bba0a8f3</citedby><cites>FETCH-LOGICAL-c457t-b24d16bcb6f6ccab1a9fb47cc13f8bc8ec4ee5bd8b80c1868ce2a6a08bba0a8f3</cites><orcidid>0000-0001-5219-9996 ; 0000-0002-7630-2123</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10262354/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10262354/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,1604,27924,27925,53791,53793</link.rule.ids><linktorsrc>$$Uhttps://dx.doi.org/10.1093/bioinformatics/btab683$$EView_record_in_Oxford_University_Press$$FView_record_in_$$GOxford_University_Press</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34601554$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Wren, Jonathan</contributor><creatorcontrib>Abrams, Zachary B</creatorcontrib><creatorcontrib>Tally, Dwayne G</creatorcontrib><creatorcontrib>Abruzzo, Lynne V</creatorcontrib><creatorcontrib>Coombes, Kevin R</creatorcontrib><title>RCytoGPS: an R package for reading and visualizing cytogenetics data</title><title>Bioinformatics</title><addtitle>Bioinformatics</addtitle><description>Abstract
Summary
Cytogenetics data, or karyotypes, are among the most common clinically used forms of genetic data. Karyotypes are stored as standardized text strings using the International System for Human Cytogenomic Nomenclature (ISCN). Historically, these data have not been used in large-scale computational analyses due to limitations in the ISCN text format and structure. Recently developed computational tools such as CytoGPS have enabled large-scale computational analyses of karyotypes. To further enable such analyses, we have now developed RCytoGPS, an R package that takes JSON files generated from CytoGPS.org and converts them into objects in R. This conversion facilitates the analysis and visualizations of karyotype data. In effect this tool streamlines the process of performing large-scale karyotype analyses, thus advancing the field of computational cytogenetic pathology.
Availability and implementation
Freely available at https://CRAN.R-project.org/package=RCytoGPS. The code for the underlying CytoGPS software can be found at https://github.com/i2-wustl/CytoGPS</description><subject>Applications Notes</subject><subject>Humans</subject><subject>Karyotype</subject><subject>Karyotyping</subject><subject>Reading</subject><subject>Software</subject><issn>1367-4803</issn><issn>1460-2059</issn><issn>1367-4811</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkcFOwzAQRC0EoqXwC1WOXELtxHZcLggVKEhIoAJna-04xZDEIU4qla8nUUtFb5y81r6ZXe0gNCb4guBpPFHW2TJzdQGN1X6iGlBcxAdoSCjHYYTZ9LCrY56EVOB4gE68_8CYEUrpMRrEHUQYo0N0s5itGzd_frkMoAwWQQX6E5Ym6KyD2kBqy2XXSIOV9S3k9rv_606xNKXpJwcpNHCKjjLIvTnbviP0dnf7OrsPH5_mD7Prx1BTljShimhKuNKKZ1xrUASmmaKJ1iTOhNLCaGoMU6lQAmsiuNAmAg5YKAUYRBaP0NXGt2pVYVJtyqaGXFa1LaBeSwdW7ndK-y6XbiUJjngUM9o5nG8davfVGt_Iwnpt8hxK41ovI5ZMsWCC9yjfoLp23tcm280hWPYZyP0M5DaDTjj-u-VO9nv0DiAbwLXVf01_ADPsnPg</recordid><startdate>20211207</startdate><enddate>20211207</enddate><creator>Abrams, Zachary B</creator><creator>Tally, Dwayne G</creator><creator>Abruzzo, Lynne V</creator><creator>Coombes, Kevin R</creator><general>Oxford University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-5219-9996</orcidid><orcidid>https://orcid.org/0000-0002-7630-2123</orcidid></search><sort><creationdate>20211207</creationdate><title>RCytoGPS: an R package for reading and visualizing cytogenetics data</title><author>Abrams, Zachary B ; Tally, Dwayne G ; Abruzzo, Lynne V ; Coombes, Kevin R</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c457t-b24d16bcb6f6ccab1a9fb47cc13f8bc8ec4ee5bd8b80c1868ce2a6a08bba0a8f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Applications Notes</topic><topic>Humans</topic><topic>Karyotype</topic><topic>Karyotyping</topic><topic>Reading</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Abrams, Zachary B</creatorcontrib><creatorcontrib>Tally, Dwayne G</creatorcontrib><creatorcontrib>Abruzzo, Lynne V</creatorcontrib><creatorcontrib>Coombes, Kevin R</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Bioinformatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Abrams, Zachary B</au><au>Tally, Dwayne G</au><au>Abruzzo, Lynne V</au><au>Coombes, Kevin R</au><au>Wren, Jonathan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>RCytoGPS: an R package for reading and visualizing cytogenetics data</atitle><jtitle>Bioinformatics</jtitle><addtitle>Bioinformatics</addtitle><date>2021-12-07</date><risdate>2021</risdate><volume>37</volume><issue>23</issue><spage>4589</spage><epage>4590</epage><pages>4589-4590</pages><issn>1367-4803</issn><eissn>1460-2059</eissn><eissn>1367-4811</eissn><abstract>Abstract
Summary
Cytogenetics data, or karyotypes, are among the most common clinically used forms of genetic data. Karyotypes are stored as standardized text strings using the International System for Human Cytogenomic Nomenclature (ISCN). Historically, these data have not been used in large-scale computational analyses due to limitations in the ISCN text format and structure. Recently developed computational tools such as CytoGPS have enabled large-scale computational analyses of karyotypes. To further enable such analyses, we have now developed RCytoGPS, an R package that takes JSON files generated from CytoGPS.org and converts them into objects in R. This conversion facilitates the analysis and visualizations of karyotype data. In effect this tool streamlines the process of performing large-scale karyotype analyses, thus advancing the field of computational cytogenetic pathology.
Availability and implementation
Freely available at https://CRAN.R-project.org/package=RCytoGPS. The code for the underlying CytoGPS software can be found at https://github.com/i2-wustl/CytoGPS</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>34601554</pmid><doi>10.1093/bioinformatics/btab683</doi><tpages>2</tpages><orcidid>https://orcid.org/0000-0001-5219-9996</orcidid><orcidid>https://orcid.org/0000-0002-7630-2123</orcidid><oa>free_for_read</oa></addata></record> |
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| language | eng |
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| source | Oxford University Press Open Access |
| subjects | Applications Notes Humans Karyotype Karyotyping Reading Software |
| title | RCytoGPS: an R package for reading and visualizing cytogenetics data |
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