gtrellis: an R/Bioconductor package for making genome-level Trellis graphics

Background Trellis graphics are a visualization method that splits data by one or more categorical variables and displays subsets of the data in a grid of panels. Trellis graphics are broadly used in genomic data analysis to compare statistics over different categories in parallel and reveal multivariate relationships. However, current software packages to produce Trellis graphics have not been designed with genomic data in mind and lack some functionality that is required for effective visualization of genomic data. Results Here we introduce the gtrellis package which provides an efficient and extensible way to visualize genomic data in a Trellis layout. gtrellis provides highly flexible Trellis layouts which allow efficient arrangement of genomic categories on the plot. It supports multiple-track visualization, which makes it straightforward to visualize several properties of genomic data in parallel to explain complex relationships. In addition, gtrellis provides an extensible framework that allows adding user-defined graphics. Conclusions The gtrellis package provides an easy and effective way to visualize genomic data and reveal high dimensional relationships on a genome-wide scale. gtrellis can be flexibly extended and thus can also serve as a base package for highly specific purposes. gtrellis makes it easy to produce novel visualizations, which can lead to the discovery of previously unrecognized patterns in genomic data. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1051-4) contains supplementary material, which is available to authorized users.

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PID https://www.doi.org/10.1186/s12859-016-1051-4
PID pmid:27089965
PID pmc:PMC4835841
URL https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4835841/
URL http://europepmc.org/articles/PMC4835841
URL https://dx.doi.org/10.1186/s12859-016-1051-4
URL https://dblp.uni-trier.de/db/journals/bmcbi/bmcbi17.html#GuES16
URL http://dx.doi.org/10.1186/s12859-016-1051-4
URL https://nbn-resolving.org/urn:nbn:de:bvb:384-opus4-792604
URL https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-016-1051-4
URL https://core.ac.uk/display/81174867
URL https://europepmc.org/articles/PMC4835841
URL https://link.springer.com/article/10.1186/s12859-016-1051-4
URL https://opus.bibliothek.uni-augsburg.de/opus4/files/79260/document.pdf
URL https://doi.org/10.1186/s12859-016-1051-4
URL https://academic.microsoft.com/#/detail/2336053812
URL https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1051-4
URL https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/79260
URL https://mdanderson.elsevierpure.com/en/publications/gtrellis-an-rbioconductor-package-for-making-genome-level-trellis
URL http://link.springer.com/content/pdf/10.1186/s12859-016-1051-4
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Access Right Open Access
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Author Matthias Schlesner, 0000-0002-5896-4086
Author Zuguang Gu, 0000-0002-7395-8709
Author Roland Eils, 0000-0002-0034-4036
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Collected From Europe PubMed Central; OPUS Augsburg; PubMed Central; ORCID; Datacite; UnpayWall; Crossref; Microsoft Academic Graph; CORE (RIOXX-UK Aggregator)
Hosted By Europe PubMed Central; SpringerOpen; OPUS Augsburg; BMC Bioinformatics
Journal BMC Bioinformatics, 17, 1
Publication Date 2016-04-18
Publisher Springer Nature
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Country Germany
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Language English
Resource Type Article; UNKNOWN
keyword ddc.ddc:610
system:type publication
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Source https://science-innovation-policy.openaire.eu/search/publication?articleId=dedup_wf_001::4aff15752199f20c4a5d989bee63f33c
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Last Updated 26 December 2020, 19:27 (CET)
Created 26 December 2020, 19:27 (CET)